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The mission of the United States Department of Transportation is to deliver the world’s leading transportation system, serving the American people and economy through the safe, efficient, sustainable, and equitable movement of people and goods.
Available DatasetsShowing 453 of 453 results
- This dataset details directly generated funding for each agency. Examples include Fares, Concessions and Advertising. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Revenue Sources database file. In years 2015-2021, you can find this data in the "Funding Sources" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- This data is the road section attribute data for HPMS. The HPMS Field Manual and HPMS 8.0 identifies a record by its Data Item. This data contains approximately 70 data items that is linked to ARNOLD through a Dynamic Segmentation process using the linear referencing components. Table 4.2 contains a list of the current Data Items.1Licence not specifiedalmost 2 years ago
- This dataset details local funding sources for each applicable agency reporting to the National Transit Database in the 2022 report year. Examples include Income, Sales, Property and Fuel taxes and Tolls. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Revenue Sources database file. In years 2015-2021, you can find this data in the "Funding Sources" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- The report includes inspections involving violations of the FMCSR or HRM.1Licence not specifiedalmost 2 years ago
- This dataset details track and roadway mileage/characteristics for each agency, mode, and type of service, as reported to the National Transit Database in Report Year 2022. These data include the types of track/roadway elements employed in transit operation, as well as the length and/or count of certain elements. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Transit Way Mileage database file. In years 2015-2021, you can find this data in the "Track and Roadway" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. In versions of the data tables from before 2015, you can find corresponding data in the file called "Transit Way Mileage - Rail Modes" and "Transit Way Mileage - Non-Rail Modes." If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- This data set comprises all TIGER grants rounds up to 20161Licence not specifiedalmost 2 years ago
- This dataset details federal funding sources for each applicable agency reporting to the NTD in Report Year 2022. Federal funding sources are financial assistance obtained from the Federal Government to assist with the costs of providing transit services. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Revenue Sources database file. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Revenue Sources database file. In years 2015-2021, you can find this data in the "Funding Sources" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- This dataset shows airports in opportunity zones.1Licence not specifiedalmost 2 years ago
- 2018 Traffic Volume Data - FHWA's TMAS Data Program (based on unweighted raw continuous traffic count information collected by state highway agencies)1Licence not specifiedalmost 2 years ago
- This dataset details capital expenses by capital use type (existing or expansion) for each applicable agency, mode, and type of service (TOS) reporting to the National Transit Database in the 2022 report year. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Capital Use database file. In years 2015-2021, you can find this data in the "Capital Expenses" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- 2019 Traffic Volume Data - FHWA's TMAS Data Program (based on unweighted raw continuous traffic count information collected by state highway agencies)1Licence not specifiedalmost 2 years ago
- The data in this data environment was collected from the Pasadena, California testbed, namely I-210, SR 134, and nearby arterials. The source of these data is from the National Center for Environmental Information – National Oceanic and Atmospheric Administration. Precipitation information from this data source is used in the cluster analysis.1Licence not specifiedalmost 2 years ago
- This dataset details operating expenses for each applicable agency, mode, and type of service (TOS), split by expense type or "Object Class" reporting to the National Transit Database in the 2022 report year.. Object classes include salaries and wages, fuel, and others. Only Full Reporters report expenses by function and type. Expenses from other reporter types are included under Reduced Reporter Expenses. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Operating Expenses database file. In years 2015-2021, you can find this data in the "Operating Expenses" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- This dataset details funding sources for each applicable agency reporting to the National Transit Database in the 2022 report year, split by fund expenditure type: capital and operating. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Revenue Sources database file. In years 2015-2021, you can find this data in the "Funding Sources" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- This dataset contains data on transit agency employees as reported to the National Transit Database in Report Year 2022. It is organized by agency, mode, type of service, and Employee Type (Full Time or Part Time Employee). The NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis This dataset is based on the 2022 annual NTD database file Employees which is published to the NTD at https://transit.dot.gov/ntd/ntd-data. Only Full Reporters report data on employees, and only for Directly Operated modes. Other reporter types, and Purchased Transportation service, do not appear in this file.1Licence not specifiedalmost 2 years ago
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- This dataset details operating expenses for each applicable agency, mode, and type of service (TOS), split by expense type reporting to the National Transit Database in the 2022 report year. Expense types include Vehicle Operations, General Administration, and more. Only Full Reporters report expenses by function and type. Expenses from other reporter types are included under Reduced Reporter Expenses. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Operating Expenses database file. In years 2015-2021, you can find this data in the "Operating Expenses" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- This a reference table for the Grade Crossing Inventory System, which is the application used to submit data for the Highway-Rail Grade Crossing Inventory (Form 71). The data dictionary for GCIS is attached as well. The LookupType column contains the name of the field/column in the source GCIS/Form 71 dataset. The LookupValue column contains the submitted value and the LookupText field is the human-readable text description of that value (e.g. for LookupType=TypeXing; LookupValue=3 and LookupText=Public, which designates that a crossing is public). This reference table can be used for the Crossing Inventory Source Data Form 71 – Current: https://datahub.transportation.gov/dataset/Crossing-Inventory-Source-Data-Form-71-Current/xp92-5xme.1Licence not specifiedalmost 2 years ago
- This dataset details maintenance facility capacities and counts for each applicable agency reporting to the National Transit Database in the 2022 report year.. Please note that because Rural Reporters are not required to report facility size counts, for these reporters null values appear under facility size columns, yet non-zero values may appear under Total Facilities. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Transit Facilities database file. In years 2015-2021, you can find this data in the "Maintenance Facilities" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- Volume of taxed special fuel, primarily diesel, but including alternative fuels, reported by the States each month, based on reports from suppliers and distributors. These amounts are reported in various Office of Highway Policy Information (OHPI) products including the longstanding Monthly Motor Fuel Report, and the annual Highway Statistics publications.1Licence not specifiedalmost 2 years ago
- This dataset details mechanical failures for each applicable agency, mode, and type of service (TOS) reporting to the National Transit Database in the 2022 report year. Only Full Reporters report breakdowns. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Vehicle Maintenance database file. In years 2015-2021, you can find this data in the "Breakdowns" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- Data is from the small-scale demonstration of the Intelligent Network Flow Optimization (INFLO) Prototype System and applications in Seattle, Washington. Connected vehicle systems were deployed in 21 vehicles in a scripted driving scenario circuiting this I-5 corridor northbound and southbound during morning rush hour. This data set contains queue warning messages that were recommended by the INFLO Q-WARN algorithm and sent by the traffic management center to vehicles to warn drivers upstream of the queue. The objective of queue warning is to provide a vehicle operator sufficient warning of impending queue backup in order to brake safely, change lanes, or modify route such that secondary collisions can be minimized or even eliminated.1Licence not specifiedalmost 2 years ago
- The data is taken from three intersections and 24 buses over a six month period in Cleveland, Ohio. The systems at the intersections provided MAP and SPAT messages and the SPAT message contained pedestrian detections from a series of cameras at the intersection. The buses received these messages and used them to alert the vehicle driver when pedestrians were about to enter the crosswalks or was in the crosswalk. The buses also used basic safety messages from external vehicles to warn the driver when another vehicle had the potential of making a right hand turn in front of the vehicle. The data contains bus locations, bus state changes, pedestrian detections and user interface state changes.1Licence not specifiedalmost 2 years ago
- The Company Census File contains records for active entities registered with FMCSA. Active entities include those entities subject to the FMCSR, HMR, or intrastate non-Hazardous Material (HM) carriers. To identify each entity, FMCSA assigns a unique number to each entity record. This number is referred to as the USDOT number. Each Census record contains entity identifying data, business operations data, equipment and driver data, and carrier review data.1Licence not specifiedalmost 2 years ago
- This dataset details fuel mileage and gallons/kilowatt hours for each agency, mode, and type of service (TOS) as reported by agencies submitted data to the National Transit Database (NTD) for Report Year 2022. This file is based on the database file 2022 Energy Consumption available at https://transit.dot.gov/ntd/ntd-data Data Tables organize and summarize data from the 2022 NTD in a manner that is more useful for quick reference and summary analysis. Only Full Reporters report energy consumption. Other reporter types do not appear in this dataset. Demand Response Taxi (DR/TX) mode and type of service combination does not report energy consumption and does not appear in this dataset. Finally, Non-dedicated fleets report energy consumption but not miles traveled. Thus for some agencies the given data for miles traveled are incomplete. Non-dedicated fleets represent about 7% of the data reflected in this dataset. In versions of the data tables from 2014-2021, you can find data on fuel and energy in the file called "Fuel and Energy" available from the NTD program website.1Licence not specifiedalmost 2 years ago
- Data is from the small-scale demonstration of the Intelligent Network Flow Optimization (INFLO) Prototype System and applications in Seattle, Washington. Connected vehicle systems were deployed in 21 vehicles in a scripted driving scenario circuiting this I-5 corridor northbound and southbound during morning rush hour. This data set contains speed harmonization messages that were recommended by the INFLO SPD-HARM algorithm and sent by the traffic management center to the connected vehicles, which provided drivers with the suggested speed while driving on the segment of I-5 that was included in the test. The objective of speed harmonization is to dynamically adjust and coordinate maximum appropriate vehicle speeds in response to downstream congestion, incidents, and weather or road conditions in order to maximize traffic throughput and reduce crashes.1Licence not specifiedalmost 2 years ago
- Contains all PDCMs generated during the AMCD field testing program. The PDCM is a control message sent from the server to OBUs to customize a request for Probe Vehicle Data (PVD) from the receiving OBU. All PDCMs are generated by the VCC Cloud server and transmitted to OBU clients through either a DSRC or cellular communications channel.1Licence not specifiedalmost 2 years ago
- 2020 Traffic Volume Data - FHWA's TMAS Data Program (based on unweighted raw continuous traffic count information collected by state highway agencies)1Licence not specifiedalmost 2 years ago
- Data is from the small-scale demonstration of the Intelligent Network Flow Optimization (INFLO) Prototype System and applications in Seattle, Washington. Connected vehicle systems were deployed in 21 vehicles in a scripted driving scenario circuiting this I-5 corridor northbound and southbound during morning rush hour. Basic Safety Messages (BSM) sent by connected vehicles (CVs) through either the cellular network or Dedicated Short Range Communication (DSRC) when the vehicle is in the range of Roadside Units (RSU). These messages were received by the traffic management center (TMC).1Licence not specifiedalmost 2 years ago
- United States Census Bureau: Cartographic Boundary Files - Shapefiles1Licence not specifiedalmost 2 years ago
- Select summary highway statistics, 1980 - 2017, mileage, lane-miles, vehicle miles traveled, and fatalities by state and functional system.1Licence not specifiedalmost 2 years ago
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- The data attached and/or displayed were collected during the Multi-Modal Intelligent Transportation Signal Systems (MMITSS) study. MMITSS is a next-generation traffic signal system that seeks to provide a comprehensive traffic information framework to service all modes of transportation. A BSM is one of the messages belonging to the Society of Automotive Engineers (SAE) J2735 Standard. This standard is geared toward supporting the interoperability of DSRC applications through the use of a standardized message set and its data frames and data elements. A BSM, which is at times referred to as a “heartbeat” message, is a frequently transmitted message (usually at approximately 10Hz) that is meant to increase a vehicle’s situational awareness. These messages are intended to be used for a variety of applications to exchange safety data regarding a vehicle’s state. A typical BSM contains up to two parts. Part I, the binary large object (blob), is included in every BSM. It contains the fundamental data elements that describe a vehicle’s position (latitude, longitude, elevation) and motion (heading, speed, acceleration). Part II of a BSM contains optional data that is transmitted when required or in response to an event. Typically Part II contains data that serves as an extension of vehicle safety information (path history, path prediction, event flags) and data pertaining to the status of a vehicle’s components, such as lights, wipers, and brakes. NOTE: All extra attachments are located in Multi-Modal Intelligent Traffic Signal Systems Basic Safety Messages such as MAP, Detectors, and Simulation results1Licence not specifiedalmost 2 years ago
- Dataset contains two subject vehicles’ trajectory data connected in naturalistic traffic conditions in central Ohio. Instrumented subject vehicles were either a discreet or readily-identifiable ADAS-equipped vehicle with SAE L2 capabilities. Dataset also contains trajectories for adjacent vehicles in traffic (observed by the subject vehicles’ onboard sensors).1Licence not specifiedalmost 2 years ago
- The Federal Highway Administration (FHWA) has been receiving Highway inventory, usage, condition and performance data from State Departments of Transportation (DOT) since 1978 to support the program mission of the FHWA. Specifically, HPMS consists of detailed road segment data (63 Attributes) for higher order systems. Sample attributes for collector systems and summary data for the local roads. New requirements for HPMS took effect in 2014 that required each State DOTs to expand their Linear Referencing Systems (LRS), a statewide geospatial representation of their road system that includes all public roads. This requirement was put in place to support highway safety. States DOTs submit HPMS data annually to the FHWA following a prescribed format outlined in the Highway Performance Monitoring System Field Manual.1Licence not specifiedalmost 2 years ago
- Volume of gasoline reported by the States each month, based on reports from suppliers and distributors. These amounts are reported in various Office of Highway Policy Information (OHPI) products including the longstanding Monthly Motor Fuel Report, and the annual Highway Statistics publications.1Licence not specifiedalmost 2 years ago
- This set of data files was acquired under USDOT FHWA cooperative agreement DTFH61-11-H-00025 as one of the four test data sets acquired by the USDOT Data Capture and Management program. This is the primary loop detector data table. It contains one-minute volume, occupancy, and data quality flags for the arterial loop detector data.1Licence not specifiedalmost 2 years ago
- This a list of active and inactive railroads, companies, and other organizations related to railroad operations. Organization Type ID = 1 designates a railroad; 4 designates a non-railroad organization (e.g. company, shipper, public entity, etc.). If a code has a blank EndDate, this means the organization is active; a populated EndDate field means the organization is no longer active.1Licence not specifiedalmost 2 years ago
- Historic Highway Performance Monitoring System sample data for the year 20041Licence not specifiedalmost 2 years ago
- The data in this data environment was collected from the Pasadena, California testbed, namely I-210, SR 134, and nearby arterials. The source of these data is from the Caltrans – Performance Measurement System (PeMS). Speed data from this dataset were used to derive the freeway travel time. There are three separate text files with one for each operational condition.1Licence not specifiedalmost 2 years ago
- Historic Highway Performance Monitoring System sample data for the year 20051Licence not specifiedalmost 2 years ago
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- This dataset details vehicle types and ages for transit agencies reporting to the National Transit Database in the 2022 report year. Vehicle types describe the vehicles employed in direct operation or support of transit service. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Revenue Vehicle Inventory and Service Vehicle Inventory database files. Rural reporters that operate in more than one state report their vehicles in only one of their states. In years 2015-2021, you can find this data in the "Vehicles" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- This dataset contains a one-month sample of flattened EVENT data records from the New York City (NYC) Connected Vehicle (CV) Pilot that have undergone obfuscation of precise time and location details as well as other vehicle identifiers. The full unflattened event data from NYC CV pilot can be found in the ITS Sandbox. Each EVENT record documents the details of one application warning that occurred on an Aftermarket Safety Device (ASD) in an equipped host vehicle and includes CV messages from a defined recording time both before and after the warning was generated by the host ASD. Messages in the recording time window include the Basic Safety Messages (BSM) of the host vehicle that received the warning, as well as other BSMs received from the warning target equipped vehicle (for V2V applications) or other nearby equipped vehicles. Depending on the application warning type, MAP messages, Signal Phase and Timing (SPaT) messages, and Traveler Information Messages (TIM) that were heard by the host vehicle may also be included in the event record.1Licence not specifiedalmost 2 years ago
- State, County and City FIPS (Federal Information Processing Standards) codes are a set of numeric designations given to state, cities and counties by the U.S. federal government. All geographic data submitted to the FRA must have a FIPS code.1Licence not specifiedalmost 2 years ago
- Historic Highway Performance Monitoring System sample data for the year 20061Licence not specifiedalmost 2 years ago
- 2017 Traffic Volume Data - FHWA's TMAS Data Program (based on unweighted raw continuous traffic count information collected by state highway agencies)1Licence not specifiedalmost 2 years ago
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- The datasets contain the subject ADAS-equipped vehicle’s trajectory collected in naturalistic traffic conditions in central Ohio. The instrumented subject vehicle was either a discreet or readily-identifiable ADAS-equipped vehicle with SAE L2 capabilities. The dataset also contains trajectories for adjacent vehicles in traffic (observed by the subject vehicle’s onboard sensors).1Licence not specifiedalmost 2 years ago
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- 2016 Traffic Volume Data - FHWA's TMAS Data Program (based on unweighted raw continuous traffic count information collected by state highway agencies)1Licence not specifiedalmost 2 years ago
- This dataset reports the historical National Highway System 50th percentile median speeds for various roadway types, months, and vehicles on US roads.1Licence not specifiedalmost 2 years ago
- Intelligent Network Flow Optimization Prototype Infrastructure Traffic Sensor System Data AggregatorData is from the small-scale demonstration of the Intelligent Network Flow Optimization (INFLO) Prototype System and applications in Seattle, Washington. Connected vehicle systems were deployed in 21 vehicles in a scripted driving scenario circuiting this I-5 corridor northbound and southbound during morning rush hour. This data set contains real-time volume, speed and loop occupancy data that were collected from WSDOT’s simulated roadway sensors every 20 seconds and aggregated according to user defined procedures and threshold by the Infrastructure Traffic Sensor System (TSS) Data Aggregator software.1Licence not specifiedalmost 2 years ago
- Massachusetts Department of Transportation (MassDOT) Work Zone Data Exchange (WZDx) v2.0 Feed SampleThis dataset provides information on work zones in the state of Massachusetts in a tabular format and is updated daily based on the live MassDOT Work Zone Data Exchange (WZDx) Feed. A continuously updating archive of the MassDOT WZDx feed data can be found at ITS WorkZone Raw Data Sandbox and the ITS WorkZone Semi-Processed Data Sandbox. The live feed is currently compliant with the WZDx Specification v2.0.1Licence not specifiedalmost 2 years ago
- Data collected on the SS-30 form. Transit agencies report to the NTD security personnel in terms of Full-Time Equivalents (FTE) according to the staffing levels at the beginning of the year. One FTE typically works 40 hours per week. An agency may use any reasonable method to allocate personnel across modes, such as allocating based on modal ridership or on modal annual trips. In certain instances, agencies may base personnel numbers on the prior year’s total hours worked.1Licence not specifiedalmost 2 years ago
- This set of data files was acquired under USDOT FHWA cooperative agreement DTFH61-11-H-00025 as one of the four test data sets acquired by the USDOT Data Capture and Management program.The freeway data consists of two months of data (Sept 15 2011 through Nov 15 2011) from dual-loop detectors deployed in the main line and on-ramps of a Portland-area freeway. The section of I-205 NB covered by this test data set is 10.09 miles long and the section of I-205 SB covered by this test data set is 12.01 miles long The data includes: flow, occupancy, and speed.1Licence not specifiedalmost 2 years ago
- This file contains a set of the fields at the Census tract level from the U.S. Census' 2017 American Community Survey 5-Year Data Profiles. The fields it includes were selected for being the most relevant to analyzing topics around transportation and equity. They cover the following topics: family structure, education, veteran status, disability, residence over the past year, foreign-born populations, language spoken at home and broadband access. Each field name contains an alphanumeric reference to the ACS table it is from, as well as a brief description of the information in the field. For example, the field DP02_0012E_households_65_living_alone comes from ACS Table DP02, and ACS numbers the field on that table as 0012E. It provides a count of households in each Census tract composed of people aged 65 and older who are living alone.1Licence not specifiedalmost 2 years ago
- This file includes event data reported to the National Transit Database (NTD) for Commuter Rail (CR) and Alaska Railroad (AR) modes, as well as Heavy Rail (HR) service reported for Port Authority Trans Hudson (NTD ID: 20098), Hybrid Rail (YR) service for the Tri-County Metropolitan Transportation District of Oregon (NTD ID: 00008), Hybrid Rail (YR) service for Denton County Transportation Authority (NTD ID: 60101), and Hybrid Rail (YR) service for Capital Metropolitan Transportation Authority (NTD ID: 60048). Because these services fall under the safety oversight of the Federal Railroad Administration, the agencies are not required to report Safety Events (e.g., collisions, derailments, etc.) to the Federal Transit Administration through the NTD. Security events occurring on transit-owned property for these entities are reported to NTD, but excluded from other files to preserve the integrity of those datasets. They are presented in this file for completeness and should be considered by any user attempting to understand the scope and scale of reportable Security Events reported by public transit operators.1Licence not specifiedalmost 2 years ago
- GPS pings collected by study participants who rode conventional and e-bikes at Minute Man National Historic Park between April and September 2022.1Licence not specifiedalmost 2 years ago
- This dataset details vehicle types and ages for each transit agency reporting to the NTD. Non-dedicated fleets do not report Year of Manufacture and are thus excluded from the Age Distribution table. Agencies do not report Useful Life Benchmark for non-dedicated fleets or fleets for which the agency does not have capital replacement responsibility. These fleets are excluded from calculations of the percentage of vehicles meeting or exceeding their useful life. In versions of the data tables from before 2014, you can find data on vehicles in the file called "Age Distribution of Active Vehicle Inventory." In years 2014-2021, you can find this data in the "Vehicles" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- Historic Highway Performance Monitoring System sample data for the year 20031Licence not specifiedalmost 2 years ago
- This dataset details service and cost efficiency metrics for agencies reporting to the National Transit Database in the 2022 report year. Only Full Reporters report data on Passenger Miles. The columns containing ratios have been calculated as the average across all reporting modes, not as the ratio of summed data. Thus, each transit agency received equal weight, regardless of that agency's total ridership. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Federal Funding Allocation, Operating Expenses, and Service database files. In years 2015-2021, you can find this data in the "Metrics" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. In versions of the NTD data tables from before 2014, you can find data on metrics in the files called "Fare per Passenger and Recovery Ratio" and "Service Supplied and Consumed Ratios." If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- Data were collected during the Multi-Modal Intelligent Transportation Signal Systems (MMITSS) study. MMITSS is a next-generation traffic signal system that seeks to provide a comprehensive traffic information framework to service all modes of transportation. The GPS data set catalogs the vehicle operation data of the test vehicles that used for the MMITSS field testing. The data contains the performance and operation details of vehicles. This file contains a number of fields detailing elements such as vehicle position and speed, fidelity measures of GPS-based data elements, and vehicle operation data. NOTE: All extra attachments are located in Multi-Modal Intelligent Traffic Signal Systems Basic Safety Message1Licence not specifiedalmost 2 years ago
- Contains metrics describing service consumption and service cost for each public transportation agency, by mode and type of service.1Licence not specifiedalmost 2 years ago
- Contains all Basic Mobility Messages (BMMs) collected during the Advanced Messaging Concept Development (AMCD) field testing program. While there is no specific standard in existence that addresses the content of a BMM, the descriptive definitions of the variables were derived from the J2735 standard where applicable. All BMMs are generated by OBUs and ultimately received by the VCC Cloud server.1Licence not specifiedalmost 2 years ago
- State DOTs will provide Local and Rural Minor Collector Mileage summarized by county, ownership, and Paved and Unpaved. This data is provided in a direct input by the State DOTs.1Licence not specifiedalmost 2 years ago
- The Belle Isle data was collected between May 1st, 2014 and September 16th, 2014 on the Belle Isle Park in Michigan. However, within the data file provided as part of this data environment, only data during the World Congress demonstration period from September 5, 2014 to September 11, 2014 is included. Several vehicles equipped with multiple sensors drove around the island collecting 572,030 readings of multiple variables. The uploaded data file lists all those observations and the pertaining details about the sensor equipment, the sensor platform and the status of quality checking performed for each observation.1Licence not specifiedalmost 2 years ago
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- Motor Vehicle Registration Data by Energy Source :2016 -Present Vehicle types are compatible with FHWA Highway Statistics VM-1 "Total" counts of vehicles for a year are compatible with FHWA Highway Statistics MV-1 minus "Motorcycle." Motorcycle data are not included.1Licence not specifiedalmost 2 years ago
- FRA develop a spatial point layer of the rail bridges over road and water. The bridges are a snapshot and is not an offical or complete inventory of all bridges. Railroads change ownership, railroads are abandoned, bridges are replaced, etc. therefore it cannot be relied upon as being accurate.1Licence not specifiedalmost 2 years ago
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- FRA develop a spatial point layer of the rail bridges over road and water. The bridges are a snapshot and is not an offical or complete inventory of all bridges. Railroads change ownership, railroads are abandoned, bridges are replaced, etc. therefore it cannot be relied upon as being accurate.1Licence not specifiedalmost 2 years ago
- Data represent the performance of prototype cooperative automated driving system applications for improving traffic mobility. The applications include the integrated highway prototype that consists of vehicle platooning, speed harmonization, and automated lane change and merge.1Licence not specifiedalmost 2 years ago
- Contains ratios describing service and cost for each agency, mode, and type of service.1Licence not specifiedalmost 2 years ago
- The FRA Milepost is a spatial file that originates of multiple sources and contains point locations of mileposts along the FRA's rail network. The mileposts was developed from varies sources and should only be used as a reference file. The railroad lines and their mileposts are privately owned and are subjected of changed based on the rail owner. If used for identifying specific locations, please contact the railroad to verify the mileposts numbers and their locations.1Licence not specifiedalmost 2 years ago
- This dataset consists of truck size and weight enforcement data including number of trucks weighed, number of violations, and number of oversize/overweight permits, as reported by the States in their annual certification to FHWA.1Licence not specifiedalmost 2 years ago
- Data were collected during the Multi-Modal Intelligent Transportation Signal Systems (MMITSS) study. MMITSS is a next-generation traffic signal system that seeks to provide a comprehensive traffic information framework to service all modes of transportation. The Vehicle Trajectories file is populated with basic safety messages received from equipped vehicle within the communication range of an Roadside Equipment (RSEs). The data also contains elements that communicate additional details about the vehicle that is used for vehicle safety applications, and elements that communicate specific items of a vehicle‘s status that are used in data event snapshots which are gathered and periodically reported to an RSEs. These data are transmitted at a rate of 10 Hz. NOTE: All extra attachments are located in Multi-Modal Intelligent Traffic Signal Systems Basic Safety Message1Licence not specifiedalmost 2 years ago
- Historic Highway Performance Monitoring System sample data for the year 20071Licence not specifiedalmost 2 years ago
- The data in this repository were collected from the San Diego, California testbed, namely, I-15 from the interchange with SR-78 in the north to the interchange with SR-163 in the south, along the mainline and at the entrance ramps. This file contains information on the field observation and simulation results for speed profile from the Dallas, Texas testbed. The time reported for the speed profiles are between 2:00PM to 8:00PM in increments of 10 minutes.1Licence not specifiedalmost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- Historic Highway Performance Monitoring System sample data for the year 20081Licence not specifiedalmost 2 years ago
- Contains all PVDs generated during the AMCD field testing program. The probe vehicle message is used to exchange status about a vehicle with other DSRC readers to allow the collection of information about a typical vehicle’s traveling behaviors along a segment of road. The exchanges of this message as well as the event which caused the collection of various elements defined in the messages are in Annex B of the SAE J2735 standard.1Licence not specifiedalmost 2 years ago
- Curated FRA Safety data pertaining to Rail Equipment Accidents (Form 54) Unique Train Accidents Please note that this dataset displays unique train accidents. When an accident involves multiple railroads, each railroad must report its data. As a result, there can be multiple records for one accident. This dataset has been modified to pull and display one record for each accident. Highway-rail crossing incidents have also been removed from this dataset because they are not considered train accidents. To see the full dataset with all reports with all data for all accidents, please visit https://data.transportation.gov/Railroads/Rail-Equipment-Accident-Incident-Data/85tf-25kj1Licence not specifiedalmost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- This data represents HPMS Sample limits that correspond to the HPMS Section Data. This dataset contains expansion factors that are used to expand the attributes to State wide aggregation. More information regarding the Sample dataset is contained in the HPMS Field Manual. The Mid-America contains data for the following States: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Oklahoma, South Dakota, Texas, and Wisconsin1Licence not specifiedalmost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- Beginning in 2023, certain agencies are required to submit one week of service data on a monthly basis to comply with FTA’s Weekly Reference reporting requirement on form WE-20. This data release will therefore present the limited set of key indicators reported by transit agencies on this form and will be updated each month with the most current data. The resulting dataset provides data users with data shortly after the transit service was provided and consumed, over one month in advance of FTA’s routine update to the Monthly Ridership Time Series dataset. One use of this data is for reference in understanding ridership patterns (e.g., to develop to a full month estimate ahead of when the data reflecting the given month of service is released by FTA at the end of the following month). Generally, FTA has defined the reference week to be the second or third full week of the month. All sampled agencies will report data referencing the same reference week. The form collects the following service data points, as described in the metadata below: • Weekday 5-day UPT total for the reference week; • Weekday 5-day VRM total for the reference week; • Weekend 2-day UPT total for either the weekend preceding or following the reference week; and • Weekend 2-day VRM total for either the weekend preceding or following the reference week. • Vehicles Operated in Maximum Service (vanpool mode only) for the reference week. FTA has also derived the change from the prior month for the same agency/mode/type of service/data point. Users should take caution when aggregating this measure and are encouraged to use the dataset export to measure service trends at a higher level (i.e., by reporter or nationally). For any questions regarding this dataset, please contact the NTD helpdesk at ntdhelp@dot.gov .1Licence not specifiedalmost 2 years ago
- Federal and State field enforcement staff performs Inspections on Interstate and Intrastate Motor Carriers and Hazardous Materials carriers. Violations of the Federal Motor Carrier Safety Regulations (FMCSRs) severe enough may result in a vehicle and/or driver being placed "out-of-service." The data collected from inspection activity is collected and stored in the FMCSA Motor Carrier Management Information System (MCMIS) Inspection Data Files. Due to privacy restrictions, driver information is not included in any inspection files released to the public.1Licence not specifiedalmost 2 years ago
- Contains all Basic Mobility Control Message (BMCMs) generated during the Advanced Messaging Concept Development (AMCD) field testing program. While there is no specific standard in existence that addresses the content of a BMCM, the following format was derived to control the configuration and content of BMMs requested from the vehicle. All BMCMs are generated by the VCC Cloud server and transmitted to OBU clients through either a DSRC or cellular communications channel.1Licence not specifiedalmost 2 years ago
- State DOTs provide the location limits of highway sections to be used to represent statewide aggregations based on a statistically valid Sample Panel. The Mid-America contains data for the following States: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Oklahoma, South Dakota, Texas, and Wisconsin.1Licence not specifiedalmost 2 years ago
- Airlines develop customer service plans that outline commitments they make in the event of a controllable delay or cancellation.1Licence not specifiedalmost 2 years ago
- Licensed driver data from Highway Statistics table DL-22, broken down by state, gender, and age group.1Licence not specifiedalmost 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Highway-Rail-Grade-Crossing-Accident-Data/7wn6-i5b9.1Licence not specifiedalmost 2 years ago
- Airlines develop customer service plans that outline commitments they make in the event of a controllable delay or cancellation.1Licence not specifiedalmost 2 years ago
- This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".1Licence not specifiedalmost 2 years ago
- ECAT - Externality Cost Estimates are the estimated costs of highway use externalities including noise, air pollution, crashes, and congestion, broken into various degrees of specificity. For each category of externality the estimates include both the total annual cost (in millions) as well as dollars per vehicle mile traveled, and can be filtered by state, highway functional system, vehicle type, urban and rural. Additionally, every figure has a low, mid, and high estimate that embodies the uncertainty in the parameters and methodology used to construct the estimates. These estimates are useful for any analysis involving the value of negative externalities of highway use, such as benefit-cost analysis or impact analysis of highway projects.1Licence not specifiedalmost 2 years ago
- almost 2 years ago
- This dataset contains a sample of the broadcast Traveler Information Messages (TIM) being generated by the Wyoming Connected Vehicle (CV) Pilot. The full set of TIMs can be found in the ITS DataHub data sandbox. Revision Note: This dataset only contains TIM sample data prior to December 18, 2018. For the most recent sample of TIM data, please refer to the Schema Version 6 dataset or retrieve the data from the ITS DataHub data sandbox.1Licence not specifiedalmost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- This dataset offers insight on weekly fluctuation of the gasoline product supply, which is an important part of any analysis of construction trends, materials and operating costs associated with highway repair and construction, and changes in traffic volume. These data come directly from the Energy Information Administration (EIA) website. The EIA publishes the average daily amount of gasoline supplied in barrels, which HPPI converts to an average number of gallons of gasoline per week.1Licence not specifiedalmost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- *Dataset* Records showing the history of each authority granted to a carrier/broker/freight forwarder, along with the dates of the original authority action (e.g., “granted”) and the final authority action (e.g., “revoked”). The dataset contains the DOT number and docket number of the entity that holds or held the authority. As there can be multiple authorities for a single entity, there may be multiple records for an entity. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- almost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- State DOT HPMS Section Attributes for Western States1Licence not specifiedalmost 2 years ago
- *Dataset* Information on carrier/broker/freight forwarder authorities that have been revoked by FMCSA. The dataset includes the DOT number and docket number of the entity, the type of authority revoked, and the reason. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- *Dataset* Records for carrier/broker/freight forwarder active or pending individual insurance policies. The records are linked to the entities by docket numbers included in the dataset. The dataset contains information on the insurance policy, including insurance company name, policy number and type of insurance. Entities can hold multiple insurance policies, so there may be multiple records associated with a particular entity. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- *Dataset* Information on the implementation dates of an active or pending insurance policy (posted date, effective date and cancel effective date). In addition to these dates, the record contains the insurance company name, the BI&PD underlying limit and maximum limit amounts, and the DOT number and docket number of the carrier/broker/freight forwarder that holds the policy. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- Historic Highway Performance Monitoring System sample data for the year 20091Licence not specifiedalmost 2 years ago
- The Tampa CV Pilot generates data from the interaction between vehicles and between vehicles and infrastructure. This dataset consists of Traveler Information Messages (TIMs) transmitted by road-side units (RSU) located throughout the Tampa CV Pilot Study area. The full set of raw, TIM data from Tampa CV Pilot can be found in the ITS Sandbox. The data fields follow a SAE J2735 TIM message structure to convey important traffic information to onboard units (OBU) of equipped vehicles. Refer to SAE J2735 Section 5.16 Message: MSG_TravelerInformation Message (TIM). This dataset holds a flattened sample of the TIM data from Tampa CV Pilot. Three additional fields were added to this Socrata dataset during ETL: a geo column (travelerdataframe_msgId_position) to allow for mapping of the geocoded TIM data within Socrata, a random number column (randomNum) to allow for random sampling of data points within Socrata, and a time of day generated column (metadata_generatedAt_timeOfDay) to allow for filtering of data by generated time.1Licence not specifiedalmost 2 years ago
- An Opportunity Zone is an economically distressed community where new investments, under certain conditions, may be eligible for preferential tax treatment. The Department of Transportation has identified transportation assets that fall within Opportunity Zones with the goal of driving investment of all types to these important areas. This dataset identifies Amtrak Stations in Opportunity Zones, and Amtrak Stations within a quarter-mile and half-mile of Opportunity Zones.1Licence not specifiedalmost 2 years ago
- Test Data of Proof-of-Concept Vehicle Platooning Based on Cooperative Adaptive Cruise Control (CACC)The data represent the performance of a proof-of-concept vehicle platooning based on the Cooperative Adaptive Cruise Control (CACC) application. The Federal Highway Administration’s Turner Fairbank Highway Research Center (TFHRC), in conjunction with the Volpe National Transportation Systems Center, tested and evaluated this prototype system in 2016. Researchers in the Saxton Transportation Operations Laboratory at TFHRC designed and built the Cooperative Automated Research Mobility Applications (CARMA) platform version 1 that enables the implementation of the proof-of-concept CACC-based platooning in passenger vehicles equipped with production adaptive cruise control, and vehicle-to-vehicle communications using dedicated short-range communications (DSRC). The data characterize the state-of-the-art capability of the CACC application based on engineering tests that were performed on closed tracks by professional drivers and using prescribed test procedures. The test data are separated into sets that correspond to test date and time, and test run number. The data include performance parameters that were collected from the CACC application and data acquisition systems, including vehicle controller area network data, CARMA's MicroAutoBox, DSRC radios, and an independent measurement system. The tests were conducted at US Army’s Aberdeen Test Center located at Aberdeen Proving Grounds, MD. Further documentation can be found here: https://rosap.ntl.bts.gov/view/dot/1038.1Licence not specifiedalmost 2 years ago
- *Dataset* Records for each BOC3 agent hired by a carrier/broker/freight forwarder. Each entity must hire a BOC3 agent to represent them in legal matters to obtain operating authority. In some cases, entities may act as their own BOC3 agent. The records in the dataset contain the BOC3 agent’s name and address. The dataset also contains the DOT number and docket number of the represented entity. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- 2015 Traffic Volume Data - FHWA's TMAS Data Program (based on unweighted raw continuous traffic count information collected by state highway agencies)1Licence not specifiedalmost 2 years ago
- *Dataset* Information on insurance forms that were rejected by FMCSA. The dataset contains information on the insurance policy associated with the form, along with the date that the form was rejected and the reason for rejection (e.g., “Policy is already cancelled”). The dataset contains the DOT number and docket number of the carrier/broker/freight forwarder associated with the policy. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- The Tampa CV Pilot generates data from the interaction between vehicles and between vehicles and infrastructure. This dataset consists of Signal Phasing and Timing Message (SPaT) Messages transmitted by road-side units (RSU) located throughout the Tampa CV Pilot Study area. The full set of raw, SPaT data from Tampa CV Pilot can be found in the ITS Sandbox. The data fields follow SAE J2735 data frames (Section 6) and structure (Section 7). This dataset holds a flattened sample of the SPaT data from Tampa CV Pilot. A column of random numbers (randomNum) was added to allow for random sampling of data points within Socrata.1Licence not specifiedalmost 2 years ago
- This dataset contains a sample of the broadcast Traveler Information Messages (TIM) being generated by the Wyoming Connected Vehicle (CV) Pilot. This dataset only contains SchemaVersion 6 TIM sample data from December 18, 2018 to present. It is updated hourly and will hold up to 3 million of the most recent TIM records. The Schema Version 6 data is described further here. For sample TIM data prior to December 18, 2018, please refer to the Schema Version 5 dataset. The full set of TIMs can be found in the ITS Sandbox.1Licence not specifiedalmost 2 years ago
- The National Bicycle Network is a geospatial dataset for nationwide bicycle routes. It is based on data and information released by public agencies such as state transportation departments, local Metropolitan Planning Organizations, local Councils of Government, city, and county public works and transportation departments. The FHWA Office of Highway Policy Information (HPPI) integrates all releases into one nationwide bicycle network, construction, and operating of such facilities as a safe, efficient, and equitable travel mode.1Licence not specifiedalmost 2 years ago
- almost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- This dataset details station/facility types and counts for each applicable agency reported to the National Transit Database for Report Year 2022. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Transit Facilities and 2022 Transit Stations database files. In years 2015-2021, you can find this data in the "Facilities and Stations" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form-55-Source-Table/unww-uhxd.1Licence not specifiedalmost 2 years ago
- During the 2014 ITS World Congress a demonstration of the connected vehicle infrastructure in the City of Detroit was conducted. The test site included approximately 14 intersections around Detroit’s COBO convention center and involved 9 equipped vehicles.Intersection Situation Data (ISD) data set communicates MAP and signal phase and timing (SPaT) information. MAP information communicates an intersection’s location (latitude and longitude), elevation, and geometric features such as approaches and lane configuration. SPaT data communicates the (current) state of the intersection’s signal indication(s). The data is composed of discrete Row Groups. A Row Group is a collection of (approximately 3-4) consecutive rows with common attribute. NOTE: All Extra Files are attached in 2014 ITS World Congress Connected Vehicle Test Bed Demonstration Vehicle Situation Data1Licence not specifiedalmost 2 years ago
- Provides detailed fare information for highest and lowest fare markets under 750 miles. For a more complete explanation, please read the introductory information at the beginning of Table 5 itself in the report (https://www.transportation.gov/office-policy/aviation-policy/domestic-airline-consumer-airfare-report-pdf).1Licence not specifiedalmost 2 years ago
- During the 2014 ITS World Congress a demonstration of the connected vehicle infrastructure in the City of Detroit was conducted. The test site included approximately 14 intersections around Detroit’s COBO convention center and involved 9 equipped vehicles. The Vehicle Situation Data (VSD) data set includes a series of data files that recorded vehicle situational data that were generated by an equipped vehicle. During the ITS World Congress, VSDs were encoded with one of two schemas. The dataset contains decoded data using both 2.0 and 2.1 ASN.1 schemas.1Licence not specifiedalmost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- During the 2014 ITS World Congress a demonstration of the connected vehicle infrastructure in the City of Detroit was conducted. The test site included approximately 14 intersections around Detroit’s COBO convention center and involved 9 equipped vehicles. Traveler Situation Data (TSD) was obtained from the data warehouse, and not the data clearinghouse. Only 19 messages were obtained from our query as the current mode of operation of the Test Bed is that the warehouse only contains a few static messages, which are meant to serve as a proxy for future operation in which query submissions will only return message(s) relevant to the context in which the query was submitted. The messages that returned per a query submission communicates a pertinent advisor message which is in part contextualized by location and content. NOTE: All Extra Files are attached in 2014 ITS World Congress Connected Vehicle Test Bed Demonstration Vehicle Situation Data1Licence not specifiedalmost 2 years ago
- The WZDx Specification enables infrastructure owners and operators (IOOs) to make harmonized work zone data available for third party use. The intent is to make travel on public roads safer and more efficient through ubiquitous access to data on work zone activity. Specifically, the project aims to get data on work zones into vehicles to help automated driving systems (ADS) and human drivers navigate more safely. MCDOT leads the effort to aggregate and collect work zone data from the AZTech Regional Partners. A continuously updating archive of the WZDx feed data can be found at ITS WorkZone Data Sandbox. The live feed is currently compliant with WZDx specification version 3.0.1Licence not specifiedalmost 2 years ago
- This dataset shows Amtrak stations in opportunity zones1Licence not specifiedalmost 2 years ago
- This dataset is a list of Department of Transportation (DOT) Artificial Intelligence (AI) use cases. Artificial intelligence (AI) promises to drive the growth of the United States economy and improve the quality of life of all Americans. Pursuant to Section 5 of Executive Order (EO) 13960, "Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government," Federal agencies are required to inventory their AI use cases and share their inventories with other government agencies and the public. In accordance with the requirements of EO 13960, this spreadsheet provides the mechanism for federal agencies to create their inaugural AI use case inventories. https://www.federalregister.gov/documents/2020/12/08/2020-27065/promoting-the-use-of-trustworthy-artificial-intelligence-in-the-federal-government1Licence not specifiedalmost 2 years ago
- Massachusetts Department of Transportation (MassDOT) Work Zone Data Exchange (WZDx) v3.1 Feed SampleThis dataset provides information on work zones in the state of Massachusetts in a tabular format and is updated daily based on the live MassDOT Work Zone Data Exchange (WZDx) Feed. A continuously updating archive of the MassDOT WZDx feed data can be found at ITS WorkZone Raw Data Sandbox and the ITS WorkZone Semi-Processed Data Sandbox. This live feed is currently compliant with the WZDx Specification v3.1.1Licence not specifiedalmost 2 years ago
- The WZDx Specification enables infrastructure owners and operators (IOOs) to make harmonized work zone data available for third party use. The intent is to make travel on public roads safer and more efficient through ubiquitous access to data on work zone activity. Specifically, the project aims to get data on work zones into vehicles to help automated driving systems (ADS) and human drivers navigate more safely. MCDOT leads the effort to aggregate and collect work zone data from the AZTech Regional Partners. A continuously updating archive of the WZDx feed data can be found at ITS WorkZone Data Sandbox. The live feed is currently compliant with WZDx specification version 1.1.1Licence not specifiedalmost 2 years ago
- Data were collected during the Multi-Modal Intelligent Transportation Signal Systems (MMITSS) study. MMITSS is a next-generation traffic signal system that seeks to provide a comprehensive traffic information framework to service all modes of transportation.The Signal Plans for Roadside Equipment (RSE) data contains the basics of a Signal Phase and Timing (SPAT) message. This data includes SPAT message and the timestamp of the SPAT message. The data also provides the signal phase and timing information for one or more movements at an intersection.1Licence not specifiedalmost 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Injury-Illness-Summary-Casualty-Data/rash-pd2d.1Licence not specifiedalmost 2 years ago
- *Dataset* Records for all carriers/brokers/freight forwarders with active, inactive, or pending authorities (common or contract). It includes the DOT number and MC/FF/MX number for the carrier/broker/freight forwarder, along with company census data (e.g., types of authority, address, types of insurance on file, and amounts of insurance on file). See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- almost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- The objective of this dataset is to create a location where there is a comprehensive list of all technologies, best practices and lessons learned from the Office of International Programs as a whole.1Licence not specifiedalmost 2 years ago
- The Tampa CV Pilot generates data from the interaction between vehicles and between vehicles and infrastructure. This dataset consists of Basic Safety Messages (BSMs) generated by participant and public transportation vehicles onboard units (OBU) and transmitted to road-side units (RSU) located throughout the Tampa CV Pilot Study area. The full set of raw, BSM data from Tampa CV Pilot can be found in the ITS Sandbox. The data fields follow SAE J2735 and J2945/1 standards and adopted units of measure. This dataset holds a flattened sample of the BSM data from Tampa CV Pilot. An extra geo column (coreData_position) was added to this dataset to allow for mapping of the geocoded BSM data within Socrata, and a column of random numbers (randomNum) was added to allow for random sampling of data points within Socrata.1Licence not specifiedalmost 2 years ago
- An Opportunity Zone is an economically distressed community where new investments, under certain conditions, may be eligible for preferential tax treatment. The Department of Transportation has identified transportation assets that fall within Opportunity Zones with the goal of driving investment of all types to these important areas. This dataset identifies Commuter Rail Stations in Opportunity Zones, and Commuter Rail Stations within a quarter-mile and half-mile of Opportunity Zones.1Licence not specifiedalmost 2 years ago
- *Dataset* This dataset contains information on a carrier’s/broker’s/freight forwarder’s previous insurance policy(ies). This dataset contains the DOT number and docket number of the entity. Additionally, it contains the cancellation method (cancelled, replaced, name change, transferred), the type of policy, the policy number, and the effective and cancellation dates of the policy. All insurance information is related to the insurance policy either being cancelled, being replaced, or prior to a name change. It is not the subsequent (if applicable) policy. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- This data set shows Amtrak industrial, office, and commercial real estate in opportunity zones1Licence not specifiedalmost 2 years ago
- Modal Service data and Safety & Security (S&S) public transit time series data delineated by transit/agency/mode/year/month. Includes all Full Reporters--transit agencies operating modes with more than 30 vehicles in maximum service--to the National Transit Database (NTD). This dataset will be updated monthly. The S&S statistics provided include both Major and Non-Major Events where applicable. This is the only NTD publication in which these totals are combined without any transformation for historical continuity.1Licence not specifiedalmost 2 years ago
- Counts of Non-Major Safety and Security Events are reported to the National Transit Database on a monthly basis, by transit agency and transit mode. These include minor fires on transit property requiring suppression, transit worker assaults not involving transport for medical attention, and other safety events that are not reportable as Major Events because a Major Event reporting threshold is not met (see Safety and Security Events dataset for a list of Major Events). In this file you will find the number of occurrences or safety incidents per month and the number of injuries in Safety Events (Safety/Security = SAF) where an individual was immediately transported away from the scene for medical attention due to those occurrences. There will be one entry for any transit mode/location with at least one occurrence for the given month. The file also contains Transit Worker Assaults which did not immediately transport away from the scene for 2023-present, as well as other Security Events (Safety/Security = SEC) reported historically but no longer collected by FTA. Note that an assault involving transport away from the scene for medical attention meets the Injury threshold and is not counted in this dataset. Agencies are not required to provide details for these events, and any description provided is omitted. The description can be available upon request. Update 5/6/24: FTA has updated its validation procedure for Non-Major S&S events to allow for inclusion in the data publication sooner in certain cases. This month, users of this dataset may notice a larger increase in S&S events than normal for certain records in 2023-2024 (only years for which data collection and validation is presently ongoing) compared to prior releases. This was done to allow for a more timely release of validated data.1Licence not specifiedalmost 2 years ago
- Data set containing all of the Federal Funding Allocation inputs submitted by NTD reporting transit agencies from 2022 to the most recently published data within the Federal Transit Administration's NTD Data website.1Licence not specifiedalmost 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data is a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Injury-Illness-Summary-Operational-Data/m8i6-zdsy.1Licence not specifiedalmost 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Rail-Equipment-Accident-Incident-Data/85tf-25kj.1Licence not specifiedalmost 2 years ago
- All Railroads covered by Part 225 Accident/Injury reporting are required to provide monthly summary statistics via the form F6180.55.1Licence not specifiedalmost 2 years ago
- This represents the Service data reported to the NTD by transit agencies to the NTD. In versions of the data tables from before 2014, you can find data on service in the file called "Transit Operating Statistics: Service Supplied and Consumed." If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- Provides fare premiums for airports in the top 1,000 city pairs, and demonstrates the impact of low-fare service and hub domination on fare levels. All records are aggregated as directionless city pair markets. Air traffic in each direction is combined. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedalmost 2 years ago
- The Highway Performance Monitoring System (HPMS) compiles data on highway network extent, use, condition, and performance. The system consists of a geospatially‐enabled database that is used to generate reports and provides tools for data analysis. Information from HPMS is used by many stakeholders across the US DOT, the Administration, Congress, and the transportation community.1Licence not specifiedalmost 2 years ago
- Contains all Basic Safety Messages (BSMs) collected during the Advanced Messaging Concept Development (AMCD) field testing program. For this project, all of the Part I BSM message fields were populated. Additional data fields were also added to the row to identify sender, time of communication, mode of communication, etc., allowing the consumer of this data set to accurately track messages through the system. All BSMs are generated by OBUs and ultimately received by the VCC Cloud server.1Licence not specifiedalmost 2 years ago
- Data summarized by city, includes the number of city-pair markets in the top 1,000 in either comparison period that involve each city, the number of passengers traveling to and from each city, the average fare, average fare per mile (yield), and average distance traveled. All records are aggregated as directionless city pair markets. All traffic traveling in both directions is added together. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedalmost 2 years ago
- This is a list of all Major Safety and Security Events from January of 2014 to the most recently published data within the Federal Transit Administration's major event time series.1Licence not specifiedalmost 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/DownloadCrossingInventoryData.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Crossing-Inventory-Data-Current/m2f8-22s6.1Licence not specifiedalmost 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form55a-Source-Table/kuvg-3uwp.1Licence not specifiedalmost 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form57-Source-Table/icqf-xf4w.1Licence not specifiedalmost 2 years ago
- Annual motor vehicle registrations by vehicle type and state, from Highway Statistics table MV-1.1Licence not specifiedalmost 2 years ago
- Tens of millions of vehicles with Takata air bags are under recall. Long-term exposure to high heat and humidity can cause these air bags to explode when deployed. Such explosions have caused injuries and deaths. NHTSA urges vehicle owners to take a few simple steps to protect themselves and others from this very serious threat to safety. This dataset tracks various progress indicators for the recall.1Licence not specifiedalmost 2 years ago
- This dataset provides information on work zones in the state of North Carolina in a tabular format and is updated daily based on the live NCDOT Work Zone Data Exchange (WZDx) Feed. A continuously updating archive of the NCDOT WZDx feed data can be found at the ITS WorkZone Raw Data Sandbox and the ITS Work Zone Semi-Processed Data Sandbox. The live feed is currently compliant with the WZDx Specification v3.1.1Licence not specifiedalmost 2 years ago
- This dataset is in a user-friendly human-readable format. It contains the historical crossing inventory. To download the current inventory data, go here: https://data.transportation.gov/Railroads/Crossing-Inventory-Data-Form-71-Current/m2f8-22s6.1Licence not specifiedalmost 2 years ago
- This dataset is in a user-friendly human-readable format. It contains the current crossing inventory - one record for each crossing. To download historical data, go here: https://data.transportation.gov/Railroads/Crossing-Inventory-Data-Historical/vhwz-raag. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Crossing-Inventory-Source-Data-Form-71-Current/xp92-5xme.1Licence not specifiedalmost 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains metadata about each data collection run. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/k74u-yqu6) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/uvrt-varj).1Licence not specifiedalmost 2 years ago
- This dataset provides lane closure occurrences within the Texas Department of Transportation (TxDOT) highway system in a tabular format. A continuously updating archive of the TxDOT WZDx feed data can be found at ITS WorkZone Raw Data Sandbox and the ITS WorkZone Semi-Processed Data Sandbox. The live feed is currently compliant with the Work Zone Data Exchange (WZDx) Specification version 2.0.1Licence not specifiedalmost 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the instantaneous data processed from radar and GPS. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/k74u-yqu6) and runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/285w-yjf5).1Licence not specifiedalmost 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the car-following instances recorded by Volpe staff. See also the runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/285w-yjf5) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/uvrt-varj).1Licence not specifiedalmost 2 years ago
- This dataset contains the up-to-date metadata on Work Zone feeds that meet the Work Zone Data Exchange (WZDx) specifications and is registered with USDOT ITS DataHub. The current work zone data from each feed can be accessed through their respective API links. Some links provide direct access, while others require a user to create their own API access key first. Please see the attached API Key Instructions document to learn how to sign up for API keys for the requisite feeds. The ITS Work Zone Sandbox, contains an archive of work zone data collected from each feed at a rate of at least every 15 minutes. This is not intended as a replacement for the work zone feeds and in many cases does not update as frequently as the feed does.1Licence not specifiedalmost 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 6 data collection runs, collected using an Instrumented Research Vehicle (IRV) along freeways and arterials in western Massachusetts in the summer of 2016 to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the instantaneous data processed from radar and GPS. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/b3k6-qwyh) and runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/74ug-57tr).1Licence not specifiedalmost 2 years ago
- Available only on the web, provides information for airport pair markets rather than city pair markets. This table only lists airport markets where the origin or destination airport is an airport that has other commercial airports in the same city. Midway Airport (MDW) and O'Hare (ORD) are examples of this. All records are aggregated as directionless markets. The combination of Airport_1 and Airport_2 define the airport pair market. All traffic traveling in both directions is added together. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedalmost 2 years ago
- This dataset contains the estimates of the vehicle miles traveled (VMT) for interstate highways and how the total travel measured by VMT compares with travel that occurred in the same week of the previous year.1Licence not specifiedalmost 2 years ago
- This is list of data elements and their attributes that are used by data assets at the Federal Highway Administration.1Licence not specifiedalmost 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 6 data collection runs, collected using an Instrumented Research Vehicle (IRV) along freeways and arterials in western Massachusetts in the summer of 2016 to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the car-following instances recorded by Volpe staff. See also the runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/b3k6-qwyh) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/4qbx-egtn).1Licence not specifiedalmost 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 6 data collection runs, collected using an Instrumented Research Vehicle (IRV) along freeways and arterials in western Massachusetts in the summer of 2016 to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains metadata about each data collection run. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/74ug-57tr) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/4qbx-egtn).1Licence not specifiedalmost 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form-54-Source-Table/aqxq-n5hy.1Licence not specifiedalmost 2 years ago
- Available on the internet only, this table is an expanded version of Table 1 that lists all city-pair markets in the contiguous United States that average at least 10 passengers each day. All records are aggregated as directionless city pair markets. All traffic traveling in both directions is added together. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedalmost 2 years ago
- About the Data: The dataset includes recall information related to specific NHTSA campaigns. Users can filter based on characteristics like manufacturer and component. The dataset can also be filtered by recall type: tires, vehicles, car seats, and equipment. The earliest campaign data is from 1966. The dataset displays the completion rate from the latest Recall Quarterly Report or Annual Report data from Year 2015 Quarter 1 (2015-1) onward. Data Reporting Requirement: Manufacturers who determine that a product or piece of original equipment either contains a safety defect or is not in compliance with Federal safety standards are required to notify NHTSA within 5 business days. NHTSA requires that manufacturers file a Defect and Noncompliance Report in compliance with Federal Regulation 49 (the National Traffic and Motor Safety Act) Part 573, which identifies the requirements for safety recalls. This information is stored in the NHTSA database referenced above. Notes: The default visualization depicted here represents only the top 12 manufacturers for the current calendar year. Please use the Filters for specific data requests. For a complete historical perspective, please visit: https://www.nhtsa.gov/sites/nhtsa.gov/files/2023-03/2022-Recalls-Annual-Report_030223-tag.pdf.1Licence not specifiedalmost 2 years ago
- Click “Export” on the right to download the vehicle trajectory data. The associated metadata and additional data can be downloaded below under "Attachments". Researchers for the Next Generation Simulation (NGSIM) program collected detailed vehicle trajectory data on southbound US 101 and Lankershim Boulevard in Los Angeles, CA, eastbound I-80 in Emeryville, CA and Peachtree Street in Atlanta, Georgia. Data was collected through a network of synchronized digital video cameras. NGVIDEO, a customized software application developed for the NGSIM program, transcribed the vehicle trajectory data from the video. This vehicle trajectory data provided the precise location of each vehicle within the study area every one-tenth of a second, resulting in detailed lane positions and locations relative to other vehicles. Click the "Show More" button below to find additional contextual data and metadata for this dataset. For site-specific NGSIM video file datasets, please see the following: - NGSIM I-80 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-I-80-Vide/2577-gpny - NGSIM US-101 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-US-101-Vi/4qzi-thur - NGSIM Lankershim Boulevard Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Lankershi/uv3e-y54k - NGSIM Peachtree Street Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Peachtree/mupt-aksf1Licence not specifiedalmost 2 years ago
- Analysis of the projects proposed by the seven finalists to USDOT's Smart City Challenge, including challenge addressed, proposed project category, and project description. The time reported for the speed profiles are between 2:00PM to 8:00PM in increments of 10 minutes.1Licence not specifiedalmost 2 years ago
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- Curated FRA Safety data pertaining to Rail Equipment Accidents (Form 54) Unique Train Accidents Please note that this dataset displays unique train accidents. When an accident involves multiple railroads, each railroad must report its data. As a result, there can be multiple records for one accident. This dataset has been modified to pull and display one record for each accident. Highway-rail crossing incidents have also been removed from this dataset because they are not considered train accidents. To see the full dataset with all reports with all data for all accidents, please visit https://data.transportation.gov/Railroads/Rail-Equipment-Accident-Incident-Data/85tf-25kj1Licence not specifiedalmost 2 years ago
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- This data represents HPMS Sample limits that correspond to the HPMS Section Data. This dataset contains expansion factors that are used to expand the attributes to State wide aggregation. More information regarding the Sample dataset is contained in the HPMS Field Manual. The Mid-America contains data for the following States: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Oklahoma, South Dakota, Texas, and Wisconsin1Licence not specifiedalmost 2 years ago
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- Federal and State field enforcement staff performs Inspections on Interstate and Intrastate Motor Carriers and Hazardous Materials carriers. Violations of the Federal Motor Carrier Safety Regulations (FMCSRs) severe enough may result in a vehicle and/or driver being placed "out-of-service." The data collected from inspection activity is collected and stored in the FMCSA Motor Carrier Management Information System (MCMIS) Inspection Data Files. Due to privacy restrictions, driver information is not included in any inspection files released to the public.1Licence not specifiedalmost 2 years ago
- State DOTs provide the location limits of highway sections to be used to represent statewide aggregations based on a statistically valid Sample Panel. The Mid-America contains data for the following States: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Oklahoma, South Dakota, Texas, and Wisconsin.1Licence not specifiedalmost 2 years ago
- Beginning in 2023, certain agencies are required to submit one week of service data on a monthly basis to comply with FTA’s Weekly Reference reporting requirement on form WE-20. This data release will therefore present the limited set of key indicators reported by transit agencies on this form and will be updated each month with the most current data. The resulting dataset provides data users with data shortly after the transit service was provided and consumed, over one month in advance of FTA’s routine update to the Monthly Ridership Time Series dataset. One use of this data is for reference in understanding ridership patterns (e.g., to develop to a full month estimate ahead of when the data reflecting the given month of service is released by FTA at the end of the following month). Generally, FTA has defined the reference week to be the second or third full week of the month. All sampled agencies will report data referencing the same reference week. The form collects the following service data points, as described in the metadata below: • Weekday 5-day UPT total for the reference week; • Weekday 5-day VRM total for the reference week; • Weekend 2-day UPT total for either the weekend preceding or following the reference week; and • Weekend 2-day VRM total for either the weekend preceding or following the reference week. • Vehicles Operated in Maximum Service (vanpool mode only) for the reference week. FTA has also derived the change from the prior month for the same agency/mode/type of service/data point. Users should take caution when aggregating this measure and are encouraged to use the dataset export to measure service trends at a higher level (i.e., by reporter or nationally). For any questions regarding this dataset, please contact the NTD helpdesk at ntdhelp@dot.gov .1Licence not specifiedalmost 2 years ago
- Contains all Basic Mobility Control Message (BMCMs) generated during the Advanced Messaging Concept Development (AMCD) field testing program. While there is no specific standard in existence that addresses the content of a BMCM, the following format was derived to control the configuration and content of BMMs requested from the vehicle. All BMCMs are generated by the VCC Cloud server and transmitted to OBU clients through either a DSRC or cellular communications channel.1Licence not specifiedalmost 2 years ago
- Airlines develop customer service plans that outline commitments they make in the event of a controllable delay or cancellation.1Licence not specifiedalmost 2 years ago
- Licensed driver data from Highway Statistics table DL-22, broken down by state, gender, and age group.1Licence not specifiedalmost 2 years ago
- Airlines develop customer service plans that outline commitments they make in the event of a controllable delay or cancellation.1Licence not specifiedalmost 2 years ago
- ECAT - Externality Cost Estimates are the estimated costs of highway use externalities including noise, air pollution, crashes, and congestion, broken into various degrees of specificity. For each category of externality the estimates include both the total annual cost (in millions) as well as dollars per vehicle mile traveled, and can be filtered by state, highway functional system, vehicle type, urban and rural. Additionally, every figure has a low, mid, and high estimate that embodies the uncertainty in the parameters and methodology used to construct the estimates. These estimates are useful for any analysis involving the value of negative externalities of highway use, such as benefit-cost analysis or impact analysis of highway projects.1Licence not specifiedalmost 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Highway-Rail-Grade-Crossing-Accident-Data/7wn6-i5b9.1Licence not specifiedalmost 2 years ago
- This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".1Licence not specifiedalmost 2 years ago
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- This dataset contains a sample of the broadcast Traveler Information Messages (TIM) being generated by the Wyoming Connected Vehicle (CV) Pilot. The full set of TIMs can be found in the ITS DataHub data sandbox. Revision Note: This dataset only contains TIM sample data prior to December 18, 2018. For the most recent sample of TIM data, please refer to the Schema Version 6 dataset or retrieve the data from the ITS DataHub data sandbox.1Licence not specifiedalmost 2 years ago
- This dataset offers insight on weekly fluctuation of the gasoline product supply, which is an important part of any analysis of construction trends, materials and operating costs associated with highway repair and construction, and changes in traffic volume. These data come directly from the Energy Information Administration (EIA) website. The EIA publishes the average daily amount of gasoline supplied in barrels, which HPPI converts to an average number of gallons of gasoline per week.1Licence not specifiedalmost 2 years ago
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- *Dataset* Records showing the history of each authority granted to a carrier/broker/freight forwarder, along with the dates of the original authority action (e.g., “granted”) and the final authority action (e.g., “revoked”). The dataset contains the DOT number and docket number of the entity that holds or held the authority. As there can be multiple authorities for a single entity, there may be multiple records for an entity. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
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- State DOT HPMS Section Attributes for Western States1Licence not specifiedalmost 2 years ago
- *Dataset* Information on carrier/broker/freight forwarder authorities that have been revoked by FMCSA. The dataset includes the DOT number and docket number of the entity, the type of authority revoked, and the reason. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- *Dataset* Records for carrier/broker/freight forwarder active or pending individual insurance policies. The records are linked to the entities by docket numbers included in the dataset. The dataset contains information on the insurance policy, including insurance company name, policy number and type of insurance. Entities can hold multiple insurance policies, so there may be multiple records associated with a particular entity. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- *Dataset* Information on the implementation dates of an active or pending insurance policy (posted date, effective date and cancel effective date). In addition to these dates, the record contains the insurance company name, the BI&PD underlying limit and maximum limit amounts, and the DOT number and docket number of the carrier/broker/freight forwarder that holds the policy. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- Historic Highway Performance Monitoring System sample data for the year 20091Licence not specifiedalmost 2 years ago
- An Opportunity Zone is an economically distressed community where new investments, under certain conditions, may be eligible for preferential tax treatment. The Department of Transportation has identified transportation assets that fall within Opportunity Zones with the goal of driving investment of all types to these important areas. This dataset identifies Amtrak Stations in Opportunity Zones, and Amtrak Stations within a quarter-mile and half-mile of Opportunity Zones.1Licence not specifiedalmost 2 years ago
- The Tampa CV Pilot generates data from the interaction between vehicles and between vehicles and infrastructure. This dataset consists of Traveler Information Messages (TIMs) transmitted by road-side units (RSU) located throughout the Tampa CV Pilot Study area. The full set of raw, TIM data from Tampa CV Pilot can be found in the ITS Sandbox. The data fields follow a SAE J2735 TIM message structure to convey important traffic information to onboard units (OBU) of equipped vehicles. Refer to SAE J2735 Section 5.16 Message: MSG_TravelerInformation Message (TIM). This dataset holds a flattened sample of the TIM data from Tampa CV Pilot. Three additional fields were added to this Socrata dataset during ETL: a geo column (travelerdataframe_msgId_position) to allow for mapping of the geocoded TIM data within Socrata, a random number column (randomNum) to allow for random sampling of data points within Socrata, and a time of day generated column (metadata_generatedAt_timeOfDay) to allow for filtering of data by generated time.1Licence not specifiedalmost 2 years ago
- Test Data of Proof-of-Concept Vehicle Platooning Based on Cooperative Adaptive Cruise Control (CACC)The data represent the performance of a proof-of-concept vehicle platooning based on the Cooperative Adaptive Cruise Control (CACC) application. The Federal Highway Administration’s Turner Fairbank Highway Research Center (TFHRC), in conjunction with the Volpe National Transportation Systems Center, tested and evaluated this prototype system in 2016. Researchers in the Saxton Transportation Operations Laboratory at TFHRC designed and built the Cooperative Automated Research Mobility Applications (CARMA) platform version 1 that enables the implementation of the proof-of-concept CACC-based platooning in passenger vehicles equipped with production adaptive cruise control, and vehicle-to-vehicle communications using dedicated short-range communications (DSRC). The data characterize the state-of-the-art capability of the CACC application based on engineering tests that were performed on closed tracks by professional drivers and using prescribed test procedures. The test data are separated into sets that correspond to test date and time, and test run number. The data include performance parameters that were collected from the CACC application and data acquisition systems, including vehicle controller area network data, CARMA's MicroAutoBox, DSRC radios, and an independent measurement system. The tests were conducted at US Army’s Aberdeen Test Center located at Aberdeen Proving Grounds, MD. Further documentation can be found here: https://rosap.ntl.bts.gov/view/dot/1038.1Licence not specifiedalmost 2 years ago
- *Dataset* Records for each BOC3 agent hired by a carrier/broker/freight forwarder. Each entity must hire a BOC3 agent to represent them in legal matters to obtain operating authority. In some cases, entities may act as their own BOC3 agent. The records in the dataset contain the BOC3 agent’s name and address. The dataset also contains the DOT number and docket number of the represented entity. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- *Dataset* Information on insurance forms that were rejected by FMCSA. The dataset contains information on the insurance policy associated with the form, along with the date that the form was rejected and the reason for rejection (e.g., “Policy is already cancelled”). The dataset contains the DOT number and docket number of the carrier/broker/freight forwarder associated with the policy. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- 2015 Traffic Volume Data - FHWA's TMAS Data Program (based on unweighted raw continuous traffic count information collected by state highway agencies)1Licence not specifiedalmost 2 years ago
- The Tampa CV Pilot generates data from the interaction between vehicles and between vehicles and infrastructure. This dataset consists of Signal Phasing and Timing Message (SPaT) Messages transmitted by road-side units (RSU) located throughout the Tampa CV Pilot Study area. The full set of raw, SPaT data from Tampa CV Pilot can be found in the ITS Sandbox. The data fields follow SAE J2735 data frames (Section 6) and structure (Section 7). This dataset holds a flattened sample of the SPaT data from Tampa CV Pilot. A column of random numbers (randomNum) was added to allow for random sampling of data points within Socrata.1Licence not specifiedalmost 2 years ago
- The National Bicycle Network is a geospatial dataset for nationwide bicycle routes. It is based on data and information released by public agencies such as state transportation departments, local Metropolitan Planning Organizations, local Councils of Government, city, and county public works and transportation departments. The FHWA Office of Highway Policy Information (HPPI) integrates all releases into one nationwide bicycle network, construction, and operating of such facilities as a safe, efficient, and equitable travel mode.1Licence not specifiedalmost 2 years ago
- This dataset contains a sample of the broadcast Traveler Information Messages (TIM) being generated by the Wyoming Connected Vehicle (CV) Pilot. This dataset only contains SchemaVersion 6 TIM sample data from December 18, 2018 to present. It is updated hourly and will hold up to 3 million of the most recent TIM records. The Schema Version 6 data is described further here. For sample TIM data prior to December 18, 2018, please refer to the Schema Version 5 dataset. The full set of TIMs can be found in the ITS Sandbox.1Licence not specifiedalmost 2 years ago
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- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form-55-Source-Table/unww-uhxd.1Licence not specifiedalmost 2 years ago
- Provides detailed fare information for highest and lowest fare markets under 750 miles. For a more complete explanation, please read the introductory information at the beginning of Table 5 itself in the report (https://www.transportation.gov/office-policy/aviation-policy/domestic-airline-consumer-airfare-report-pdf).1Licence not specifiedalmost 2 years ago
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- The WZDx Specification enables infrastructure owners and operators (IOOs) to make harmonized work zone data available for third party use. The intent is to make travel on public roads safer and more efficient through ubiquitous access to data on work zone activity. Specifically, the project aims to get data on work zones into vehicles to help automated driving systems (ADS) and human drivers navigate more safely. MCDOT leads the effort to aggregate and collect work zone data from the AZTech Regional Partners. A continuously updating archive of the WZDx feed data can be found at ITS WorkZone Data Sandbox. The live feed is currently compliant with WZDx specification version 3.0.1Licence not specifiedalmost 2 years ago
- This dataset details station/facility types and counts for each applicable agency reported to the National Transit Database for Report Year 2022. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Transit Facilities and 2022 Transit Stations database files. In years 2015-2021, you can find this data in the "Facilities and Stations" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- During the 2014 ITS World Congress a demonstration of the connected vehicle infrastructure in the City of Detroit was conducted. The test site included approximately 14 intersections around Detroit’s COBO convention center and involved 9 equipped vehicles.Intersection Situation Data (ISD) data set communicates MAP and signal phase and timing (SPaT) information. MAP information communicates an intersection’s location (latitude and longitude), elevation, and geometric features such as approaches and lane configuration. SPaT data communicates the (current) state of the intersection’s signal indication(s). The data is composed of discrete Row Groups. A Row Group is a collection of (approximately 3-4) consecutive rows with common attribute. NOTE: All Extra Files are attached in 2014 ITS World Congress Connected Vehicle Test Bed Demonstration Vehicle Situation Data1Licence not specifiedalmost 2 years ago
- During the 2014 ITS World Congress a demonstration of the connected vehicle infrastructure in the City of Detroit was conducted. The test site included approximately 14 intersections around Detroit’s COBO convention center and involved 9 equipped vehicles. The Vehicle Situation Data (VSD) data set includes a series of data files that recorded vehicle situational data that were generated by an equipped vehicle. During the ITS World Congress, VSDs were encoded with one of two schemas. The dataset contains decoded data using both 2.0 and 2.1 ASN.1 schemas.1Licence not specifiedalmost 2 years ago
- During the 2014 ITS World Congress a demonstration of the connected vehicle infrastructure in the City of Detroit was conducted. The test site included approximately 14 intersections around Detroit’s COBO convention center and involved 9 equipped vehicles. Traveler Situation Data (TSD) was obtained from the data warehouse, and not the data clearinghouse. Only 19 messages were obtained from our query as the current mode of operation of the Test Bed is that the warehouse only contains a few static messages, which are meant to serve as a proxy for future operation in which query submissions will only return message(s) relevant to the context in which the query was submitted. The messages that returned per a query submission communicates a pertinent advisor message which is in part contextualized by location and content. NOTE: All Extra Files are attached in 2014 ITS World Congress Connected Vehicle Test Bed Demonstration Vehicle Situation Data1Licence not specifiedalmost 2 years ago
- This dataset shows Amtrak stations in opportunity zones1Licence not specifiedalmost 2 years ago
- Massachusetts Department of Transportation (MassDOT) Work Zone Data Exchange (WZDx) v3.1 Feed SampleThis dataset provides information on work zones in the state of Massachusetts in a tabular format and is updated daily based on the live MassDOT Work Zone Data Exchange (WZDx) Feed. A continuously updating archive of the MassDOT WZDx feed data can be found at ITS WorkZone Raw Data Sandbox and the ITS WorkZone Semi-Processed Data Sandbox. This live feed is currently compliant with the WZDx Specification v3.1.1Licence not specifiedalmost 2 years ago
- This dataset is a list of Department of Transportation (DOT) Artificial Intelligence (AI) use cases. Artificial intelligence (AI) promises to drive the growth of the United States economy and improve the quality of life of all Americans. Pursuant to Section 5 of Executive Order (EO) 13960, "Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government," Federal agencies are required to inventory their AI use cases and share their inventories with other government agencies and the public. In accordance with the requirements of EO 13960, this spreadsheet provides the mechanism for federal agencies to create their inaugural AI use case inventories. https://www.federalregister.gov/documents/2020/12/08/2020-27065/promoting-the-use-of-trustworthy-artificial-intelligence-in-the-federal-government1Licence not specifiedalmost 2 years ago
- The WZDx Specification enables infrastructure owners and operators (IOOs) to make harmonized work zone data available for third party use. The intent is to make travel on public roads safer and more efficient through ubiquitous access to data on work zone activity. Specifically, the project aims to get data on work zones into vehicles to help automated driving systems (ADS) and human drivers navigate more safely. MCDOT leads the effort to aggregate and collect work zone data from the AZTech Regional Partners. A continuously updating archive of the WZDx feed data can be found at ITS WorkZone Data Sandbox. The live feed is currently compliant with WZDx specification version 1.1.1Licence not specifiedalmost 2 years ago
- Data were collected during the Multi-Modal Intelligent Transportation Signal Systems (MMITSS) study. MMITSS is a next-generation traffic signal system that seeks to provide a comprehensive traffic information framework to service all modes of transportation.The Signal Plans for Roadside Equipment (RSE) data contains the basics of a Signal Phase and Timing (SPAT) message. This data includes SPAT message and the timestamp of the SPAT message. The data also provides the signal phase and timing information for one or more movements at an intersection.1Licence not specifiedalmost 2 years ago
- *Dataset* Records for all carriers/brokers/freight forwarders with active, inactive, or pending authorities (common or contract). It includes the DOT number and MC/FF/MX number for the carrier/broker/freight forwarder, along with company census data (e.g., types of authority, address, types of insurance on file, and amounts of insurance on file). See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Injury-Illness-Summary-Casualty-Data/rash-pd2d.1Licence not specifiedalmost 2 years ago
- almost 2 years ago
- The objective of this dataset is to create a location where there is a comprehensive list of all technologies, best practices and lessons learned from the Office of International Programs as a whole.1Licence not specifiedalmost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- The Tampa CV Pilot generates data from the interaction between vehicles and between vehicles and infrastructure. This dataset consists of Basic Safety Messages (BSMs) generated by participant and public transportation vehicles onboard units (OBU) and transmitted to road-side units (RSU) located throughout the Tampa CV Pilot Study area. The full set of raw, BSM data from Tampa CV Pilot can be found in the ITS Sandbox. The data fields follow SAE J2735 and J2945/1 standards and adopted units of measure. This dataset holds a flattened sample of the BSM data from Tampa CV Pilot. An extra geo column (coreData_position) was added to this dataset to allow for mapping of the geocoded BSM data within Socrata, and a column of random numbers (randomNum) was added to allow for random sampling of data points within Socrata.1Licence not specifiedalmost 2 years ago
- An Opportunity Zone is an economically distressed community where new investments, under certain conditions, may be eligible for preferential tax treatment. The Department of Transportation has identified transportation assets that fall within Opportunity Zones with the goal of driving investment of all types to these important areas. This dataset identifies Commuter Rail Stations in Opportunity Zones, and Commuter Rail Stations within a quarter-mile and half-mile of Opportunity Zones.1Licence not specifiedalmost 2 years ago
- *Dataset* This dataset contains information on a carrier’s/broker’s/freight forwarder’s previous insurance policy(ies). This dataset contains the DOT number and docket number of the entity. Additionally, it contains the cancellation method (cancelled, replaced, name change, transferred), the type of policy, the policy number, and the effective and cancellation dates of the policy. All insurance information is related to the insurance policy either being cancelled, being replaced, or prior to a name change. It is not the subsequent (if applicable) policy. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.1Licence not specifiedalmost 2 years ago
- This data set shows Amtrak industrial, office, and commercial real estate in opportunity zones1Licence not specifiedalmost 2 years ago
- Counts of Non-Major Safety and Security Events are reported to the National Transit Database on a monthly basis, by transit agency and transit mode. These include minor fires on transit property requiring suppression, transit worker assaults not involving transport for medical attention, and other safety events that are not reportable as Major Events because a Major Event reporting threshold is not met (see Safety and Security Events dataset for a list of Major Events). In this file you will find the number of occurrences or safety incidents per month and the number of injuries in Safety Events (Safety/Security = SAF) where an individual was immediately transported away from the scene for medical attention due to those occurrences. There will be one entry for any transit mode/location with at least one occurrence for the given month. The file also contains Transit Worker Assaults which did not immediately transport away from the scene for 2023-present, as well as other Security Events (Safety/Security = SEC) reported historically but no longer collected by FTA. Note that an assault involving transport away from the scene for medical attention meets the Injury threshold and is not counted in this dataset. Agencies are not required to provide details for these events, and any description provided is omitted. The description can be available upon request. Update 5/6/24: FTA has updated its validation procedure for Non-Major S&S events to allow for inclusion in the data publication sooner in certain cases. This month, users of this dataset may notice a larger increase in S&S events than normal for certain records in 2023-2024 (only years for which data collection and validation is presently ongoing) compared to prior releases. This was done to allow for a more timely release of validated data.1Licence not specifiedalmost 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data is a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Injury-Illness-Summary-Operational-Data/m8i6-zdsy.1Licence not specifiedalmost 2 years ago
- All Railroads covered by Part 225 Accident/Injury reporting are required to provide monthly summary statistics via the form F6180.55.1Licence not specifiedalmost 2 years ago
- 1Licence not specifiedalmost 2 years ago
- Modal Service data and Safety & Security (S&S) public transit time series data delineated by transit/agency/mode/year/month. Includes all Full Reporters--transit agencies operating modes with more than 30 vehicles in maximum service--to the National Transit Database (NTD). This dataset will be updated monthly. The S&S statistics provided include both Major and Non-Major Events where applicable. This is the only NTD publication in which these totals are combined without any transformation for historical continuity.1Licence not specifiedalmost 2 years ago
- Data set containing all of the Federal Funding Allocation inputs submitted by NTD reporting transit agencies from 2022 to the most recently published data within the Federal Transit Administration's NTD Data website.1Licence not specifiedalmost 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Rail-Equipment-Accident-Incident-Data/85tf-25kj.1Licence not specifiedalmost 2 years ago
- This represents the Service data reported to the NTD by transit agencies to the NTD. In versions of the data tables from before 2014, you can find data on service in the file called "Transit Operating Statistics: Service Supplied and Consumed." If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedalmost 2 years ago
- Provides fare premiums for airports in the top 1,000 city pairs, and demonstrates the impact of low-fare service and hub domination on fare levels. All records are aggregated as directionless city pair markets. Air traffic in each direction is combined. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedalmost 2 years ago
- Contains all Basic Safety Messages (BSMs) collected during the Advanced Messaging Concept Development (AMCD) field testing program. For this project, all of the Part I BSM message fields were populated. Additional data fields were also added to the row to identify sender, time of communication, mode of communication, etc., allowing the consumer of this data set to accurately track messages through the system. All BSMs are generated by OBUs and ultimately received by the VCC Cloud server.1Licence not specifiedalmost 2 years ago
- This is a list of all Major Safety and Security Events from January of 2014 to the most recently published data within the Federal Transit Administration's major event time series.1Licence not specifiedalmost 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form55a-Source-Table/kuvg-3uwp.1Licence not specifiedalmost 2 years ago
- Annual motor vehicle registrations by vehicle type and state, from Highway Statistics table MV-1.1Licence not specifiedalmost 2 years ago
- This dataset provides information on work zones in the state of North Carolina in a tabular format and is updated daily based on the live NCDOT Work Zone Data Exchange (WZDx) Feed. A continuously updating archive of the NCDOT WZDx feed data can be found at the ITS WorkZone Raw Data Sandbox and the ITS Work Zone Semi-Processed Data Sandbox. The live feed is currently compliant with the WZDx Specification v3.1.1Licence not specifiedalmost 2 years ago
- The Highway Performance Monitoring System (HPMS) compiles data on highway network extent, use, condition, and performance. The system consists of a geospatially‐enabled database that is used to generate reports and provides tools for data analysis. Information from HPMS is used by many stakeholders across the US DOT, the Administration, Congress, and the transportation community.1Licence not specifiedalmost 2 years ago
- Data summarized by city, includes the number of city-pair markets in the top 1,000 in either comparison period that involve each city, the number of passengers traveling to and from each city, the average fare, average fare per mile (yield), and average distance traveled. All records are aggregated as directionless city pair markets. All traffic traveling in both directions is added together. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedalmost 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/DownloadCrossingInventoryData.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Crossing-Inventory-Data-Current/m2f8-22s6.1Licence not specifiedalmost 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form57-Source-Table/icqf-xf4w.1Licence not specifiedalmost 2 years ago
- Tens of millions of vehicles with Takata air bags are under recall. Long-term exposure to high heat and humidity can cause these air bags to explode when deployed. Such explosions have caused injuries and deaths. NHTSA urges vehicle owners to take a few simple steps to protect themselves and others from this very serious threat to safety. This dataset tracks various progress indicators for the recall.1Licence not specifiedalmost 2 years ago
- This dataset is in a user-friendly human-readable format. It contains the historical crossing inventory. To download the current inventory data, go here: https://data.transportation.gov/Railroads/Crossing-Inventory-Data-Form-71-Current/m2f8-22s6.1Licence not specifiedalmost 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains metadata about each data collection run. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/k74u-yqu6) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/uvrt-varj).1Licence not specifiedalmost 2 years ago
- This dataset is in a user-friendly human-readable format. It contains the current crossing inventory - one record for each crossing. To download historical data, go here: https://data.transportation.gov/Railroads/Crossing-Inventory-Data-Historical/vhwz-raag. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Crossing-Inventory-Source-Data-Form-71-Current/xp92-5xme.1Licence not specifiedalmost 2 years ago
- This dataset provides lane closure occurrences within the Texas Department of Transportation (TxDOT) highway system in a tabular format. A continuously updating archive of the TxDOT WZDx feed data can be found at ITS WorkZone Raw Data Sandbox and the ITS WorkZone Semi-Processed Data Sandbox. The live feed is currently compliant with the Work Zone Data Exchange (WZDx) Specification version 2.0.1Licence not specifiedalmost 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the car-following instances recorded by Volpe staff. See also the runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/285w-yjf5) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/uvrt-varj).1Licence not specifiedalmost 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 6 data collection runs, collected using an Instrumented Research Vehicle (IRV) along freeways and arterials in western Massachusetts in the summer of 2016 to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the instantaneous data processed from radar and GPS. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/b3k6-qwyh) and runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/74ug-57tr).1Licence not specifiedalmost 2 years ago
- This dataset contains the estimates of the vehicle miles traveled (VMT) for interstate highways and how the total travel measured by VMT compares with travel that occurred in the same week of the previous year.1Licence not specifiedalmost 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the instantaneous data processed from radar and GPS. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/k74u-yqu6) and runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/285w-yjf5).1Licence not specifiedalmost 2 years ago
- This dataset contains the up-to-date metadata on Work Zone feeds that meet the Work Zone Data Exchange (WZDx) specifications and is registered with USDOT ITS DataHub. The current work zone data from each feed can be accessed through their respective API links. Some links provide direct access, while others require a user to create their own API access key first. Please see the attached API Key Instructions document to learn how to sign up for API keys for the requisite feeds. The ITS Work Zone Sandbox, contains an archive of work zone data collected from each feed at a rate of at least every 15 minutes. This is not intended as a replacement for the work zone feeds and in many cases does not update as frequently as the feed does.1Licence not specifiedalmost 2 years ago
- Available only on the web, provides information for airport pair markets rather than city pair markets. This table only lists airport markets where the origin or destination airport is an airport that has other commercial airports in the same city. Midway Airport (MDW) and O'Hare (ORD) are examples of this. All records are aggregated as directionless markets. The combination of Airport_1 and Airport_2 define the airport pair market. All traffic traveling in both directions is added together. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedalmost 2 years ago
- This is list of data elements and their attributes that are used by data assets at the Federal Highway Administration.1Licence not specifiedalmost 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 6 data collection runs, collected using an Instrumented Research Vehicle (IRV) along freeways and arterials in western Massachusetts in the summer of 2016 to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains metadata about each data collection run. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/74ug-57tr) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/4qbx-egtn).1Licence not specifiedalmost 2 years ago
- Available on the internet only, this table is an expanded version of Table 1 that lists all city-pair markets in the contiguous United States that average at least 10 passengers each day. All records are aggregated as directionless city pair markets. All traffic traveling in both directions is added together. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedalmost 2 years ago
- Click “Export” on the right to download the vehicle trajectory data. The associated metadata and additional data can be downloaded below under "Attachments". Researchers for the Next Generation Simulation (NGSIM) program collected detailed vehicle trajectory data on southbound US 101 and Lankershim Boulevard in Los Angeles, CA, eastbound I-80 in Emeryville, CA and Peachtree Street in Atlanta, Georgia. Data was collected through a network of synchronized digital video cameras. NGVIDEO, a customized software application developed for the NGSIM program, transcribed the vehicle trajectory data from the video. This vehicle trajectory data provided the precise location of each vehicle within the study area every one-tenth of a second, resulting in detailed lane positions and locations relative to other vehicles. Click the "Show More" button below to find additional contextual data and metadata for this dataset. For site-specific NGSIM video file datasets, please see the following: - NGSIM I-80 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-I-80-Vide/2577-gpny - NGSIM US-101 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-US-101-Vi/4qzi-thur - NGSIM Lankershim Boulevard Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Lankershi/uv3e-y54k - NGSIM Peachtree Street Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Peachtree/mupt-aksf1Licence not specifiedalmost 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 6 data collection runs, collected using an Instrumented Research Vehicle (IRV) along freeways and arterials in western Massachusetts in the summer of 2016 to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the car-following instances recorded by Volpe staff. See also the runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/b3k6-qwyh) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/4qbx-egtn).1Licence not specifiedalmost 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form-54-Source-Table/aqxq-n5hy.1Licence not specifiedalmost 2 years ago
- About the Data: The dataset includes recall information related to specific NHTSA campaigns. Users can filter based on characteristics like manufacturer and component. The dataset can also be filtered by recall type: tires, vehicles, car seats, and equipment. The earliest campaign data is from 1966. The dataset displays the completion rate from the latest Recall Quarterly Report or Annual Report data from Year 2015 Quarter 1 (2015-1) onward. Data Reporting Requirement: Manufacturers who determine that a product or piece of original equipment either contains a safety defect or is not in compliance with Federal safety standards are required to notify NHTSA within 5 business days. NHTSA requires that manufacturers file a Defect and Noncompliance Report in compliance with Federal Regulation 49 (the National Traffic and Motor Safety Act) Part 573, which identifies the requirements for safety recalls. This information is stored in the NHTSA database referenced above. Notes: The default visualization depicted here represents only the top 12 manufacturers for the current calendar year. Please use the Filters for specific data requests. For a complete historical perspective, please visit: https://www.nhtsa.gov/sites/nhtsa.gov/files/2023-03/2022-Recalls-Annual-Report_030223-tag.pdf.1Licence not specifiedalmost 2 years ago
- Analysis of the projects proposed by the seven finalists to USDOT's Smart City Challenge, including challenge addressed, proposed project category, and project description. The time reported for the speed profiles are between 2:00PM to 8:00PM in increments of 10 minutes.1Licence not specifiedalmost 2 years ago
- This dataset details funding sources for each applicable agency reporting to the National Transit Database in the 2022 report year, split by fund expenditure type: capital and operating. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Revenue Sources database file. In years 2015-2021, you can find this data in the "Funding Sources" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedabout 2 years ago
- 1Licence not specifiedabout 2 years ago
- This a reference table for the Grade Crossing Inventory System, which is the application used to submit data for the Highway-Rail Grade Crossing Inventory (Form 71). The data dictionary for GCIS is attached as well. The LookupType column contains the name of the field/column in the source GCIS/Form 71 dataset. The LookupValue column contains the submitted value and the LookupText field is the human-readable text description of that value (e.g. for LookupType=TypeXing; LookupValue=3 and LookupText=Public, which designates that a crossing is public). This reference table can be used for the Crossing Inventory Source Data Form 71 – Current: https://datahub.transportation.gov/dataset/Crossing-Inventory-Source-Data-Form-71-Current/xp92-5xme.1Licence not specifiedabout 2 years ago
- Data were collected during the Multi-Modal Intelligent Transportation Signal Systems (MMITSS) study. MMITSS is a next-generation traffic signal system that seeks to provide a comprehensive traffic information framework to service all modes of transportation.The Signal Plans for Roadside Equipment (RSE) data contains the basics of a Signal Phase and Timing (SPAT) message. This data includes SPAT message and the timestamp of the SPAT message. The data also provides the signal phase and timing information for one or more movements at an intersection.1Licence not specifiedabout 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Injury-Illness-Summary-Casualty-Data/rash-pd2d.1Licence not specifiedabout 2 years ago
- about 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Rail-Equipment-Accident-Incident-Data/85tf-25kj.1Licence not specifiedabout 2 years ago
- The Tampa CV Pilot generates data from the interaction between vehicles and between vehicles and infrastructure. This dataset consists of Basic Safety Messages (BSMs) generated by participant and public transportation vehicles onboard units (OBU) and transmitted to road-side units (RSU) located throughout the Tampa CV Pilot Study area. The full set of raw, BSM data from Tampa CV Pilot can be found in the ITS Sandbox. The data fields follow SAE J2735 and J2945/1 standards and adopted units of measure. This dataset holds a flattened sample of the BSM data from Tampa CV Pilot. An extra geo column (coreData_position) was added to this dataset to allow for mapping of the geocoded BSM data within Socrata, and a column of random numbers (randomNum) was added to allow for random sampling of data points within Socrata.1Licence not specifiedabout 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data is a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Injury-Illness-Summary-Operational-Data/m8i6-zdsy.1Licence not specifiedabout 2 years ago
- The objective of this dataset is to create a location where there is a comprehensive list of all technologies, best practices and lessons learned from the Office of International Programs as a whole.1Licence not specifiedabout 2 years ago
- An Opportunity Zone is an economically distressed community where new investments, under certain conditions, may be eligible for preferential tax treatment. The Department of Transportation has identified transportation assets that fall within Opportunity Zones with the goal of driving investment of all types to these important areas. This dataset identifies Commuter Rail Stations in Opportunity Zones, and Commuter Rail Stations within a quarter-mile and half-mile of Opportunity Zones.1Licence not specifiedabout 2 years ago
- This dataset contains the monthly median speeds for the National Highway System for various function classes, areas and vehicles on US roads.1Licence not specifiedabout 2 years ago
- This data set shows Amtrak industrial, office, and commercial real estate in opportunity zones1Licence not specifiedabout 2 years ago
- 1Licence not specifiedabout 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/DownloadCrossingInventoryData.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Crossing-Inventory-Data-Current/m2f8-22s6.1Licence not specifiedabout 2 years ago
- Modal Service data and Safety & Security (S&S) public transit time series data delineated by transit/agency/mode/year/month. Includes all Full Reporters--transit agencies operating modes with more than 30 vehicles in maximum service--to the National Transit Database (NTD). This dataset will be updated monthly. The S&S statistics provided include both Major and Non-Major Events where applicable. This is the only NTD publication in which these totals are combined without any transformation for historical continuity.1Licence not specifiedabout 2 years ago
- Counts of Non-Major Safety and Security Events are reported to the National Transit Database on a monthly basis, by transit agency and transit mode. These include minor fires on transit property requiring suppression, transit worker assaults not involving transport for medical attention, and other safety events that are not reportable as Major Events because a Major Event reporting threshold is not met (see Safety and Security Events dataset for a list of Major Events). In this file you will find the number of occurrences or safety incidents per month and the number of injuries in Safety Events (Safety/Security = SAF) where an individual was immediately transported away from the scene for medical attention due to those occurrences. There will be one entry for any transit mode/location with at least one occurrence for the given month. The file also contains Transit Worker Assaults which did not immediately transport away from the scene for 2023-present, as well as other Security Events (Safety/Security = SEC) reported historically but no longer collected by FTA. Note that an assault involving transport away from the scene for medical attention meets the Injury threshold and is not counted in this dataset. Agencies are not required to provide details for these events, and any description provided is omitted. The description can be available upon request.1Licence not specifiedabout 2 years ago
- Data set containing all of the Federal Funding Allocation inputs submitted by NTD reporting transit agencies from 2022 to the most recently published data within the Federal Transit Administration's NTD Data website.1Licence not specifiedabout 2 years ago
- This represents the Service data reported to the NTD by transit agencies to the NTD. In versions of the data tables from before 2014, you can find data on service in the file called "Transit Operating Statistics: Service Supplied and Consumed." If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedabout 2 years ago
- All Railroads covered by Part 225 Accident/Injury reporting are required to provide monthly summary statistics via the form F6180.55.1Licence not specifiedabout 2 years ago
- Provides fare premiums for airports in the top 1,000 city pairs, and demonstrates the impact of low-fare service and hub domination on fare levels. All records are aggregated as directionless city pair markets. Air traffic in each direction is combined. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedabout 2 years ago
- The Highway Performance Monitoring System (HPMS) compiles data on highway network extent, use, condition, and performance. The system consists of a geospatially‐enabled database that is used to generate reports and provides tools for data analysis. Information from HPMS is used by many stakeholders across the US DOT, the Administration, Congress, and the transportation community.1Licence not specifiedabout 2 years ago
- Contains all Basic Safety Messages (BSMs) collected during the Advanced Messaging Concept Development (AMCD) field testing program. For this project, all of the Part I BSM message fields were populated. Additional data fields were also added to the row to identify sender, time of communication, mode of communication, etc., allowing the consumer of this data set to accurately track messages through the system. All BSMs are generated by OBUs and ultimately received by the VCC Cloud server.1Licence not specifiedabout 2 years ago
- Data summarized by city, includes the number of city-pair markets in the top 1,000 in either comparison period that involve each city, the number of passengers traveling to and from each city, the average fare, average fare per mile (yield), and average distance traveled. All records are aggregated as directionless city pair markets. All traffic traveling in both directions is added together. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedabout 2 years ago
- This is a list of all Major Safety and Security Events from January of 2014 to the most recently published data within the Federal Transit Administration's major event time series.1Licence not specifiedabout 2 years ago
- Annual motor vehicle registrations by vehicle type and state, from Highway Statistics table MV-1.1Licence not specifiedabout 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form55a-Source-Table/kuvg-3uwp.1Licence not specifiedabout 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form57-Source-Table/icqf-xf4w.1Licence not specifiedabout 2 years ago
- This dataset is in a user-friendly human-readable format. It contains the historical crossing inventory. To download the current inventory data, go here: https://data.transportation.gov/Railroads/Crossing-Inventory-Data-Form-71-Current/m2f8-22s6.1Licence not specifiedabout 2 years ago
- This dataset provides information on work zones in the state of North Carolina in a tabular format and is updated daily based on the live NCDOT Work Zone Data Exchange (WZDx) Feed. A continuously updating archive of the NCDOT WZDx feed data can be found at the ITS WorkZone Raw Data Sandbox and the ITS Work Zone Semi-Processed Data Sandbox. The live feed is currently compliant with the WZDx Specification v3.1.1Licence not specifiedabout 2 years ago
- Tens of millions of vehicles with Takata air bags are under recall. Long-term exposure to high heat and humidity can cause these air bags to explode when deployed. Such explosions have caused injuries and deaths. NHTSA urges vehicle owners to take a few simple steps to protect themselves and others from this very serious threat to safety. This dataset tracks various progress indicators for the recall.1Licence not specifiedabout 2 years ago
- This dataset is in a user-friendly human-readable format. It contains the current crossing inventory - one record for each crossing. To download historical data, go here: https://data.transportation.gov/Railroads/Crossing-Inventory-Data-Historical/vhwz-raag. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Crossing-Inventory-Source-Data-Form-71-Current/xp92-5xme.1Licence not specifiedabout 2 years ago
- This dataset contains the up-to-date metadata on Work Zone feeds that meet the Work Zone Data Exchange (WZDx) specifications and is registered with USDOT ITS DataHub. The current work zone data from each feed can be accessed through their respective API links. Some links provide direct access, while others require a user to create their own API access key first. Please see the attached API Key Instructions document to learn how to sign up for API keys for the requisite feeds. The ITS Work Zone Sandbox, contains an archive of work zone data collected from each feed at a rate of at least every 15 minutes. This is not intended as a replacement for the work zone feeds and in many cases does not update as frequently as the feed does.1Licence not specifiedabout 2 years ago
- This dataset provides lane closure occurrences within the Texas Department of Transportation (TxDOT) highway system in a tabular format. A continuously updating archive of the TxDOT WZDx feed data can be found at ITS WorkZone Raw Data Sandbox and the ITS WorkZone Semi-Processed Data Sandbox. The live feed is currently compliant with the Work Zone Data Exchange (WZDx) Specification version 2.0.1Licence not specifiedabout 2 years ago
- This dataset contains the estimates of the vehicle miles traveled (VMT) for interstate highways and how the total travel measured by VMT compares with travel that occurred in the same week of the previous year.1Licence not specifiedabout 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains metadata about each data collection run. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/k74u-yqu6) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/uvrt-varj).1Licence not specifiedabout 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the instantaneous data processed from radar and GPS. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/k74u-yqu6) and runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/285w-yjf5).1Licence not specifiedabout 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the car-following instances recorded by Volpe staff. See also the runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/285w-yjf5) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/uvrt-varj).1Licence not specifiedabout 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form-54-Source-Table/aqxq-n5hy.1Licence not specifiedabout 2 years ago
- Available only on the web, provides information for airport pair markets rather than city pair markets. This table only lists airport markets where the origin or destination airport is an airport that has other commercial airports in the same city. Midway Airport (MDW) and O'Hare (ORD) are examples of this. All records are aggregated as directionless markets. The combination of Airport_1 and Airport_2 define the airport pair market. All traffic traveling in both directions is added together. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedabout 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 6 data collection runs, collected using an Instrumented Research Vehicle (IRV) along freeways and arterials in western Massachusetts in the summer of 2016 to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the instantaneous data processed from radar and GPS. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/b3k6-qwyh) and runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/74ug-57tr).1Licence not specifiedabout 2 years ago
- This is list of data elements and their attributes that are used by data assets at the Federal Highway Administration.1Licence not specifiedabout 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 6 data collection runs, collected using an Instrumented Research Vehicle (IRV) along freeways and arterials in western Massachusetts in the summer of 2016 to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains metadata about each data collection run. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/74ug-57tr) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/4qbx-egtn).1Licence not specifiedabout 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 6 data collection runs, collected using an Instrumented Research Vehicle (IRV) along freeways and arterials in western Massachusetts in the summer of 2016 to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the car-following instances recorded by Volpe staff. See also the runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/b3k6-qwyh) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/4qbx-egtn).1Licence not specifiedabout 2 years ago
- Available on the internet only, this table is an expanded version of Table 1 that lists all city-pair markets in the contiguous United States that average at least 10 passengers each day. All records are aggregated as directionless city pair markets. All traffic traveling in both directions is added together. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedabout 2 years ago
- About the Data: The dataset includes recall information related to specific NHTSA campaigns. Users can filter based on characteristics like manufacturer and component. The dataset can also be filtered by recall type: tires, vehicles, car seats, and equipment. The earliest campaign data is from 1966. The dataset displays the completion rate from the latest Recall Quarterly Report or Annual Report data from Year 2015 Quarter 1 (2015-1) onward. Data Reporting Requirement: Manufacturers who determine that a product or piece of original equipment either contains a safety defect or is not in compliance with Federal safety standards are required to notify NHTSA within 5 business days. NHTSA requires that manufacturers file a Defect and Noncompliance Report in compliance with Federal Regulation 49 (the National Traffic and Motor Safety Act) Part 573, which identifies the requirements for safety recalls. This information is stored in the NHTSA database referenced above. Notes: The default visualization depicted here represents only the top 12 manufacturers for the current calendar year. Please use the Filters for specific data requests. For a complete historical perspective, please visit: https://www.nhtsa.gov/sites/nhtsa.gov/files/2023-03/2022-Recalls-Annual-Report_030223-tag.pdf.1Licence not specifiedabout 2 years ago
- Click “Export” on the right to download the vehicle trajectory data. The associated metadata and additional data can be downloaded below under "Attachments". Researchers for the Next Generation Simulation (NGSIM) program collected detailed vehicle trajectory data on southbound US 101 and Lankershim Boulevard in Los Angeles, CA, eastbound I-80 in Emeryville, CA and Peachtree Street in Atlanta, Georgia. Data was collected through a network of synchronized digital video cameras. NGVIDEO, a customized software application developed for the NGSIM program, transcribed the vehicle trajectory data from the video. This vehicle trajectory data provided the precise location of each vehicle within the study area every one-tenth of a second, resulting in detailed lane positions and locations relative to other vehicles. Click the "Show More" button below to find additional contextual data and metadata for this dataset. For site-specific NGSIM video file datasets, please see the following: - NGSIM I-80 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-I-80-Vide/2577-gpny - NGSIM US-101 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-US-101-Vi/4qzi-thur - NGSIM Lankershim Boulevard Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Lankershi/uv3e-y54k - NGSIM Peachtree Street Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Peachtree/mupt-aksf1Licence not specifiedabout 2 years ago
- Analysis of the projects proposed by the seven finalists to USDOT's Smart City Challenge, including challenge addressed, proposed project category, and project description. The time reported for the speed profiles are between 2:00PM to 8:00PM in increments of 10 minutes.1Licence not specifiedabout 2 years ago
- This dataset consists of truck size and weight enforcement data including number of trucks weighed, number of violations, and number of oversize/overweight permits, as reported by the States in their annual certification to FHWA.1Licence not specifiedabout 2 years ago
- Data were collected during the Multi-Modal Intelligent Transportation Signal Systems (MMITSS) study. MMITSS is a next-generation traffic signal system that seeks to provide a comprehensive traffic information framework to service all modes of transportation. The Vehicle Trajectories file is populated with basic safety messages received from equipped vehicle within the communication range of an Roadside Equipment (RSEs). The data also contains elements that communicate additional details about the vehicle that is used for vehicle safety applications, and elements that communicate specific items of a vehicle‘s status that are used in data event snapshots which are gathered and periodically reported to an RSEs. These data are transmitted at a rate of 10 Hz. NOTE: All extra attachments are located in Multi-Modal Intelligent Traffic Signal Systems Basic Safety Message1Licence not specifiedabout 2 years ago
- Historic Highway Performance Monitoring System sample data for the year 20081Licence not specifiedabout 2 years ago
- The data in this repository were collected from the San Diego, California testbed, namely, I-15 from the interchange with SR-78 in the north to the interchange with SR-163 in the south, along the mainline and at the entrance ramps. This file contains information on the field observation and simulation results for speed profile from the Dallas, Texas testbed. The time reported for the speed profiles are between 2:00PM to 8:00PM in increments of 10 minutes.1Licence not specifiedabout 2 years ago
- Licensed driver data from Highway Statistics table DL-22, broken down by state, gender, and age group.1Licence not specifiedabout 2 years ago
- This data represents HPMS Sample limits that correspond to the HPMS Section Data. This dataset contains expansion factors that are used to expand the attributes to State wide aggregation. More information regarding the Sample dataset is contained in the HPMS Field Manual. The Mid-America contains data for the following States: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Oklahoma, South Dakota, Texas, and Wisconsin1Licence not specifiedabout 2 years ago
- Contains ratios describing service and cost for each agency, mode, and type of service.1Licence not specifiedabout 2 years ago
- Historic Highway Performance Monitoring System sample data for the year 20071Licence not specifiedabout 2 years ago
- Contains all PVDs generated during the AMCD field testing program. The probe vehicle message is used to exchange status about a vehicle with other DSRC readers to allow the collection of information about a typical vehicle’s traveling behaviors along a segment of road. The exchanges of this message as well as the event which caused the collection of various elements defined in the messages are in Annex B of the SAE J2735 standard.1Licence not specifiedabout 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Highway-Rail-Grade-Crossing-Accident-Data/7wn6-i5b9.1Licence not specifiedabout 2 years ago
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- State DOTs provide the location limits of highway sections to be used to represent statewide aggregations based on a statistically valid Sample Panel. The Mid-America contains data for the following States: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Oklahoma, South Dakota, Texas, and Wisconsin.1Licence not specifiedabout 2 years ago
- This dataset contains a sample of the broadcast Traveler Information Messages (TIM) being generated by the Wyoming Connected Vehicle (CV) Pilot. The full set of TIMs can be found in the ITS DataHub data sandbox. Revision Note: This dataset only contains TIM sample data prior to December 18, 2018. For the most recent sample of TIM data, please refer to the Schema Version 6 dataset or retrieve the data from the ITS DataHub data sandbox.1Licence not specifiedabout 2 years ago
- Airlines develop customer service plans that outline commitments they make in the event of a controllable delay or cancellation.1Licence not specifiedabout 2 years ago
- about 2 years ago
- Beginning in 2023, certain agencies are required to submit one week of service data on a monthly basis to comply with FTA’s Weekly Reference reporting requirement on form WE-20. This data release will therefore present the limited set of key indicators reported by transit agencies on this form and will be updated each month with the most current data. The resulting dataset provides data users with data shortly after the transit service was provided and consumed, over one month in advance of FTA’s routine update to the Monthly Ridership Time Series dataset. One use of this data is for reference in understanding ridership patterns (e.g., to develop to a full month estimate ahead of when the data reflecting the given month of service is released by FTA at the end of the following month). Generally, FTA has defined the reference week to be the second or third full week of the month. All sampled agencies will report data referencing the same reference week. The form collects the following service data points, as described in the metadata below: • Weekday 5-day UPT total for the reference week; • Weekday 5-day VRM total for the reference week; • Weekend 2-day UPT total for either the weekend preceding or following the reference week; and • Weekend 2-day VRM total for either the weekend preceding or following the reference week. • Vehicles Operated in Maximum Service (vanpool mode only) for the reference week. FTA has also derived the change from the prior month for the same agency/mode/type of service/data point. Users should take caution when aggregating this measure and are encouraged to use the dataset export to measure service trends at a higher level (i.e., by reporter or nationally). For any questions regarding this dataset, please contact the NTD helpdesk at ntdhelp@dot.gov .1Licence not specifiedabout 2 years ago
- 1Licence not specifiedabout 2 years ago
- Airlines develop customer service plans that outline commitments they make in the event of a controllable delay or cancellation.1Licence not specifiedabout 2 years ago
- This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".1Licence not specifiedabout 2 years ago
- ECAT - Externality Cost Estimates are the estimated costs of highway use externalities including noise, air pollution, crashes, and congestion, broken into various degrees of specificity. For each category of externality the estimates include both the total annual cost (in millions) as well as dollars per vehicle mile traveled, and can be filtered by state, highway functional system, vehicle type, urban and rural. Additionally, every figure has a low, mid, and high estimate that embodies the uncertainty in the parameters and methodology used to construct the estimates. These estimates are useful for any analysis involving the value of negative externalities of highway use, such as benefit-cost analysis or impact analysis of highway projects.1Licence not specifiedabout 2 years ago
- about 2 years ago
- 1Licence not specifiedabout 2 years ago
- 1Licence not specifiedabout 2 years ago
- 1Licence not specifiedabout 2 years ago
- This dataset offers insight on weekly fluctuation of the gasoline product supply, which is an important part of any analysis of construction trends, materials and operating costs associated with highway repair and construction, and changes in traffic volume. These data come directly from the Energy Information Administration (EIA) website. The EIA publishes the average daily amount of gasoline supplied in barrels, which HPPI converts to an average number of gallons of gasoline per week.1Licence not specifiedabout 2 years ago
- about 2 years ago
- 1Licence not specifiedabout 2 years ago
- State DOT HPMS Section Attributes for Western States1Licence not specifiedabout 2 years ago
- An Opportunity Zone is an economically distressed community where new investments, under certain conditions, may be eligible for preferential tax treatment. The Department of Transportation has identified transportation assets that fall within Opportunity Zones with the goal of driving investment of all types to these important areas. This dataset identifies Amtrak Stations in Opportunity Zones, and Amtrak Stations within a quarter-mile and half-mile of Opportunity Zones.1Licence not specifiedabout 2 years ago
- 2015 Traffic Volume Data - FHWA's TMAS Data Program (based on unweighted raw continuous traffic count information collected by state highway agencies)1Licence not specifiedabout 2 years ago
- Historic Highway Performance Monitoring System sample data for the year 20091Licence not specifiedabout 2 years ago
- The Tampa CV Pilot generates data from the interaction between vehicles and between vehicles and infrastructure. This dataset consists of Traveler Information Messages (TIMs) transmitted by road-side units (RSU) located throughout the Tampa CV Pilot Study area. The full set of raw, TIM data from Tampa CV Pilot can be found in the ITS Sandbox. The data fields follow a SAE J2735 TIM message structure to convey important traffic information to onboard units (OBU) of equipped vehicles. Refer to SAE J2735 Section 5.16 Message: MSG_TravelerInformation Message (TIM). This dataset holds a flattened sample of the TIM data from Tampa CV Pilot. Three additional fields were added to this Socrata dataset during ETL: a geo column (travelerdataframe_msgId_position) to allow for mapping of the geocoded TIM data within Socrata, a random number column (randomNum) to allow for random sampling of data points within Socrata, and a time of day generated column (metadata_generatedAt_timeOfDay) to allow for filtering of data by generated time.1Licence not specifiedabout 2 years ago
- Test Data of Proof-of-Concept Vehicle Platooning Based on Cooperative Adaptive Cruise Control (CACC)The data represent the performance of a proof-of-concept vehicle platooning based on the Cooperative Adaptive Cruise Control (CACC) application. The Federal Highway Administration’s Turner Fairbank Highway Research Center (TFHRC), in conjunction with the Volpe National Transportation Systems Center, tested and evaluated this prototype system in 2016. Researchers in the Saxton Transportation Operations Laboratory at TFHRC designed and built the Cooperative Automated Research Mobility Applications (CARMA) platform version 1 that enables the implementation of the proof-of-concept CACC-based platooning in passenger vehicles equipped with production adaptive cruise control, and vehicle-to-vehicle communications using dedicated short-range communications (DSRC). The data characterize the state-of-the-art capability of the CACC application based on engineering tests that were performed on closed tracks by professional drivers and using prescribed test procedures. The test data are separated into sets that correspond to test date and time, and test run number. The data include performance parameters that were collected from the CACC application and data acquisition systems, including vehicle controller area network data, CARMA's MicroAutoBox, DSRC radios, and an independent measurement system. The tests were conducted at US Army’s Aberdeen Test Center located at Aberdeen Proving Grounds, MD. Further documentation can be found here: https://rosap.ntl.bts.gov/view/dot/1038.1Licence not specifiedabout 2 years ago
- The Tampa CV Pilot generates data from the interaction between vehicles and between vehicles and infrastructure. This dataset consists of Signal Phasing and Timing Message (SPaT) Messages transmitted by road-side units (RSU) located throughout the Tampa CV Pilot Study area. The full set of raw, SPaT data from Tampa CV Pilot can be found in the ITS Sandbox. The data fields follow SAE J2735 data frames (Section 6) and structure (Section 7). This dataset holds a flattened sample of the SPaT data from Tampa CV Pilot. A column of random numbers (randomNum) was added to allow for random sampling of data points within Socrata.1Licence not specifiedabout 2 years ago
- This dataset is a list of Department of Transportation (DOT) Artificial Intelligence (AI) use cases. Artificial intelligence (AI) promises to drive the growth of the United States economy and improve the quality of life of all Americans. Pursuant to Section 5 of Executive Order (EO) 13960, "Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government," Federal agencies are required to inventory their AI use cases and share their inventories with other government agencies and the public. In accordance with the requirements of EO 13960, this spreadsheet provides the mechanism for federal agencies to create their inaugural AI use case inventories. https://www.federalregister.gov/documents/2020/12/08/2020-27065/promoting-the-use-of-trustworthy-artificial-intelligence-in-the-federal-government1Licence not specifiedabout 2 years ago
- about 2 years ago
- This dataset contains a sample of the broadcast Traveler Information Messages (TIM) being generated by the Wyoming Connected Vehicle (CV) Pilot. This dataset only contains SchemaVersion 6 TIM sample data from December 18, 2018 to present. It is updated hourly and will hold up to 3 million of the most recent TIM records. The Schema Version 6 data is described further here. For sample TIM data prior to December 18, 2018, please refer to the Schema Version 5 dataset. The full set of TIMs can be found in the ITS Sandbox.1Licence not specifiedabout 2 years ago
- This dataset details station/facility types and counts for each applicable agency reported to the National Transit Database for Report Year 2022. NTD Data Tables organize and summarize data from the 2022 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 Transit Facilities and 2022 Transit Stations database files. In years 2015-2021, you can find this data in the "Facilities and Stations" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data. If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedabout 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form-55-Source-Table/unww-uhxd.1Licence not specifiedabout 2 years ago
- about 2 years ago
- During the 2014 ITS World Congress a demonstration of the connected vehicle infrastructure in the City of Detroit was conducted. The test site included approximately 14 intersections around Detroit’s COBO convention center and involved 9 equipped vehicles. The Vehicle Situation Data (VSD) data set includes a series of data files that recorded vehicle situational data that were generated by an equipped vehicle. During the ITS World Congress, VSDs were encoded with one of two schemas. The dataset contains decoded data using both 2.0 and 2.1 ASN.1 schemas.1Licence not specifiedabout 2 years ago
- 1Licence not specifiedabout 2 years ago
- about 2 years ago
- During the 2014 ITS World Congress a demonstration of the connected vehicle infrastructure in the City of Detroit was conducted. The test site included approximately 14 intersections around Detroit’s COBO convention center and involved 9 equipped vehicles.Intersection Situation Data (ISD) data set communicates MAP and signal phase and timing (SPaT) information. MAP information communicates an intersection’s location (latitude and longitude), elevation, and geometric features such as approaches and lane configuration. SPaT data communicates the (current) state of the intersection’s signal indication(s). The data is composed of discrete Row Groups. A Row Group is a collection of (approximately 3-4) consecutive rows with common attribute. NOTE: All Extra Files are attached in 2014 ITS World Congress Connected Vehicle Test Bed Demonstration Vehicle Situation Data1Licence not specifiedabout 2 years ago
- Provides detailed fare information for highest and lowest fare markets under 750 miles. For a more complete explanation, please read the introductory information at the beginning of Table 5 itself in the report (https://www.transportation.gov/office-policy/aviation-policy/domestic-airline-consumer-airfare-report-pdf).1Licence not specifiedabout 2 years ago
- The WZDx Specification enables infrastructure owners and operators (IOOs) to make harmonized work zone data available for third party use. The intent is to make travel on public roads safer and more efficient through ubiquitous access to data on work zone activity. Specifically, the project aims to get data on work zones into vehicles to help automated driving systems (ADS) and human drivers navigate more safely. MCDOT leads the effort to aggregate and collect work zone data from the AZTech Regional Partners. A continuously updating archive of the WZDx feed data can be found at ITS WorkZone Data Sandbox. The live feed is currently compliant with WZDx specification version 3.0.1Licence not specifiedabout 2 years ago
- This dataset shows Amtrak stations in opportunity zones1Licence not specifiedabout 2 years ago
- The objective of this dataset is to create a location where there is a comprehensive list of all technologies, best practices and lessons learned from the Office of International Programs as a whole.1Licence not specifiedabout 2 years ago
- This dataset contains the monthly median speeds for the National Highway System for various function classes, areas and vehicles on US roads.1Licence not specifiedabout 2 years ago
- Data were collected during the Multi-Modal Intelligent Transportation Signal Systems (MMITSS) study. MMITSS is a next-generation traffic signal system that seeks to provide a comprehensive traffic information framework to service all modes of transportation.The Signal Plans for Roadside Equipment (RSE) data contains the basics of a Signal Phase and Timing (SPAT) message. This data includes SPAT message and the timestamp of the SPAT message. The data also provides the signal phase and timing information for one or more movements at an intersection.1Licence not specifiedabout 2 years ago
- about 2 years ago
- The Tampa CV Pilot generates data from the interaction between vehicles and between vehicles and infrastructure. This dataset consists of Basic Safety Messages (BSMs) generated by participant and public transportation vehicles onboard units (OBU) and transmitted to road-side units (RSU) located throughout the Tampa CV Pilot Study area. The full set of raw, BSM data from Tampa CV Pilot can be found in the ITS Sandbox. The data fields follow SAE J2735 and J2945/1 standards and adopted units of measure. This dataset holds a flattened sample of the BSM data from Tampa CV Pilot. An extra geo column (coreData_position) was added to this dataset to allow for mapping of the geocoded BSM data within Socrata, and a column of random numbers (randomNum) was added to allow for random sampling of data points within Socrata.1Licence not specifiedabout 2 years ago
- The WZDx Specification enables infrastructure owners and operators (IOOs) to make harmonized work zone data available for third party use. The intent is to make travel on public roads safer and more efficient through ubiquitous access to data on work zone activity. Specifically, the project aims to get data on work zones into vehicles to help automated driving systems (ADS) and human drivers navigate more safely. MCDOT leads the effort to aggregate and collect work zone data from the AZTech Regional Partners. A continuously updating archive of the WZDx feed data can be found at ITS WorkZone Data Sandbox. The live feed is currently compliant with WZDx specification version 1.1.1Licence not specifiedabout 2 years ago
- Massachusetts Department of Transportation (MassDOT) Work Zone Data Exchange (WZDx) v3.1 Feed SampleThis dataset provides information on work zones in the state of Massachusetts in a tabular format and is updated daily based on the live MassDOT Work Zone Data Exchange (WZDx) Feed. A continuously updating archive of the MassDOT WZDx feed data can be found at ITS WorkZone Raw Data Sandbox and the ITS WorkZone Semi-Processed Data Sandbox. This live feed is currently compliant with the WZDx Specification v3.1.1Licence not specifiedabout 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Injury-Illness-Summary-Casualty-Data/rash-pd2d.1Licence not specifiedabout 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Rail-Equipment-Accident-Incident-Data/85tf-25kj.1Licence not specifiedabout 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/on_the_fly_download.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data is a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Injury-Illness-Summary-Operational-Data/m8i6-zdsy.1Licence not specifiedabout 2 years ago
- An Opportunity Zone is an economically distressed community where new investments, under certain conditions, may be eligible for preferential tax treatment. The Department of Transportation has identified transportation assets that fall within Opportunity Zones with the goal of driving investment of all types to these important areas. This dataset identifies Commuter Rail Stations in Opportunity Zones, and Commuter Rail Stations within a quarter-mile and half-mile of Opportunity Zones.1Licence not specifiedabout 2 years ago
- This data set shows Amtrak industrial, office, and commercial real estate in opportunity zones1Licence not specifiedabout 2 years ago
- During the 2014 ITS World Congress a demonstration of the connected vehicle infrastructure in the City of Detroit was conducted. The test site included approximately 14 intersections around Detroit’s COBO convention center and involved 9 equipped vehicles. Traveler Situation Data (TSD) was obtained from the data warehouse, and not the data clearinghouse. Only 19 messages were obtained from our query as the current mode of operation of the Test Bed is that the warehouse only contains a few static messages, which are meant to serve as a proxy for future operation in which query submissions will only return message(s) relevant to the context in which the query was submitted. The messages that returned per a query submission communicates a pertinent advisor message which is in part contextualized by location and content. NOTE: All Extra Files are attached in 2014 ITS World Congress Connected Vehicle Test Bed Demonstration Vehicle Situation Data1Licence not specifiedabout 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/DownloadCrossingInventoryData.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Crossing-Inventory-Data-Current/m2f8-22s6.1Licence not specifiedabout 2 years ago
- Counts of Non-Major Safety and Security Events are reported to the National Transit Database on a monthly basis, by transit agency and transit mode. These include minor fires on transit property requiring suppression, transit worker assaults not involving transport for medical attention, and other safety events that are not reportable as Major Events because a Major Event reporting threshold is not met (see Safety and Security Events dataset for a list of Major Events). In this file you will find the number of occurrences or safety incidents per month and the number of injuries in Safety Events (Safety/Security = SAF) where an individual was immediately transported away from the scene for medical attention due to those occurrences. There will be one entry for any transit mode/location with at least one occurrence for the given month. The file also contains Transit Worker Assaults which did not immediately transport away from the scene for 2023-present, as well as other Security Events (Safety/Security = SEC) reported historically but no longer collected by FTA. Note that an assault involving transport away from the scene for medical attention meets the Injury threshold and is not counted in this dataset. Agencies are not required to provide details for these events, and any description provided is omitted. The description can be available upon request.1Licence not specifiedabout 2 years ago
- This represents the Service data reported to the NTD by transit agencies to the NTD. In versions of the data tables from before 2014, you can find data on service in the file called "Transit Operating Statistics: Service Supplied and Consumed." If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedabout 2 years ago
- Provides fare premiums for airports in the top 1,000 city pairs, and demonstrates the impact of low-fare service and hub domination on fare levels. All records are aggregated as directionless city pair markets. Air traffic in each direction is combined. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedabout 2 years ago
- Contains all Basic Safety Messages (BSMs) collected during the Advanced Messaging Concept Development (AMCD) field testing program. For this project, all of the Part I BSM message fields were populated. Additional data fields were also added to the row to identify sender, time of communication, mode of communication, etc., allowing the consumer of this data set to accurately track messages through the system. All BSMs are generated by OBUs and ultimately received by the VCC Cloud server.1Licence not specifiedabout 2 years ago
- This is a list of all Major Safety and Security Events from January of 2014 to the most recently published data within the Federal Transit Administration's major event time series.1Licence not specifiedabout 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form55a-Source-Table/kuvg-3uwp.1Licence not specifiedabout 2 years ago
- This dataset is in a user-friendly human-readable format. It contains the historical crossing inventory. To download the current inventory data, go here: https://data.transportation.gov/Railroads/Crossing-Inventory-Data-Form-71-Current/m2f8-22s6.1Licence not specifiedabout 2 years ago
- Tens of millions of vehicles with Takata air bags are under recall. Long-term exposure to high heat and humidity can cause these air bags to explode when deployed. Such explosions have caused injuries and deaths. NHTSA urges vehicle owners to take a few simple steps to protect themselves and others from this very serious threat to safety. This dataset tracks various progress indicators for the recall.1Licence not specifiedabout 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form-54-Source-Table/aqxq-n5hy.1Licence not specifiedabout 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 6 data collection runs, collected using an Instrumented Research Vehicle (IRV) along freeways and arterials in western Massachusetts in the summer of 2016 to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the instantaneous data processed from radar and GPS. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/b3k6-qwyh) and runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/74ug-57tr).1Licence not specifiedabout 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 6 data collection runs, collected using an Instrumented Research Vehicle (IRV) along freeways and arterials in western Massachusetts in the summer of 2016 to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains metadata about each data collection run. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/74ug-57tr) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/4qbx-egtn).1Licence not specifiedabout 2 years ago
- Available on the internet only, this table is an expanded version of Table 1 that lists all city-pair markets in the contiguous United States that average at least 10 passengers each day. All records are aggregated as directionless city pair markets. All traffic traveling in both directions is added together. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedabout 2 years ago
- Click “Export” on the right to download the vehicle trajectory data. The associated metadata and additional data can be downloaded below under "Attachments". Researchers for the Next Generation Simulation (NGSIM) program collected detailed vehicle trajectory data on southbound US 101 and Lankershim Boulevard in Los Angeles, CA, eastbound I-80 in Emeryville, CA and Peachtree Street in Atlanta, Georgia. Data was collected through a network of synchronized digital video cameras. NGVIDEO, a customized software application developed for the NGSIM program, transcribed the vehicle trajectory data from the video. This vehicle trajectory data provided the precise location of each vehicle within the study area every one-tenth of a second, resulting in detailed lane positions and locations relative to other vehicles. Click the "Show More" button below to find additional contextual data and metadata for this dataset. For site-specific NGSIM video file datasets, please see the following: - NGSIM I-80 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-I-80-Vide/2577-gpny - NGSIM US-101 Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-US-101-Vi/4qzi-thur - NGSIM Lankershim Boulevard Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Lankershi/uv3e-y54k - NGSIM Peachtree Street Videos: https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Program-Peachtree/mupt-aksf1Licence not specifiedabout 2 years ago
- This dataset contains the up-to-date metadata on Work Zone feeds that meet the Work Zone Data Exchange (WZDx) specifications and is registered with USDOT ITS DataHub. The current work zone data from each feed can be accessed through their respective API links. Some links provide direct access, while others require a user to create their own API access key first. Please see the attached API Key Instructions document to learn how to sign up for API keys for the requisite feeds. The ITS Work Zone Sandbox, contains an archive of work zone data collected from each feed at a rate of at least every 15 minutes. This is not intended as a replacement for the work zone feeds and in many cases does not update as frequently as the feed does.1Licence not specifiedabout 2 years ago
- This dataset contains the estimates of the vehicle miles traveled (VMT) for interstate highways and how the total travel measured by VMT compares with travel that occurred in the same week of the previous year.1Licence not specifiedabout 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the instantaneous data processed from radar and GPS. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/k74u-yqu6) and runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/285w-yjf5).1Licence not specifiedabout 2 years ago
- 1Licence not specifiedabout 2 years ago
- Modal Service data and Safety & Security (S&S) public transit time series data delineated by transit/agency/mode/year/month. Includes all Full Reporters--transit agencies operating modes with more than 30 vehicles in maximum service--to the National Transit Database (NTD). This dataset will be updated monthly. The S&S statistics provided include both Major and Non-Major Events where applicable. This is the only NTD publication in which these totals are combined without any transformation for historical continuity.1Licence not specifiedabout 2 years ago
- Data set containing all of the Federal Funding Allocation inputs submitted by NTD reporting transit agencies from 2022 to the most recently published data within the Federal Transit Administration's NTD Data website.1Licence not specifiedabout 2 years ago
- All Railroads covered by Part 225 Accident/Injury reporting are required to provide monthly summary statistics via the form F6180.55.1Licence not specifiedabout 2 years ago
- The Highway Performance Monitoring System (HPMS) compiles data on highway network extent, use, condition, and performance. The system consists of a geospatially‐enabled database that is used to generate reports and provides tools for data analysis. Information from HPMS is used by many stakeholders across the US DOT, the Administration, Congress, and the transportation community.1Licence not specifiedabout 2 years ago
- Data summarized by city, includes the number of city-pair markets in the top 1,000 in either comparison period that involve each city, the number of passengers traveling to and from each city, the average fare, average fare per mile (yield), and average distance traveled. All records are aggregated as directionless city pair markets. All traffic traveling in both directions is added together. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedabout 2 years ago
- Annual motor vehicle registrations by vehicle type and state, from Highway Statistics table MV-1.1Licence not specifiedabout 2 years ago
- This dataset is in a user-friendly human-readable format. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Form57-Source-Table/icqf-xf4w.1Licence not specifiedabout 2 years ago
- This dataset provides information on work zones in the state of North Carolina in a tabular format and is updated daily based on the live NCDOT Work Zone Data Exchange (WZDx) Feed. A continuously updating archive of the NCDOT WZDx feed data can be found at the ITS WorkZone Raw Data Sandbox and the ITS Work Zone Semi-Processed Data Sandbox. The live feed is currently compliant with the WZDx Specification v3.1.1Licence not specifiedabout 2 years ago
- This dataset is in a user-friendly human-readable format. It contains the current crossing inventory - one record for each crossing. To download historical data, go here: https://data.transportation.gov/Railroads/Crossing-Inventory-Data-Historical/vhwz-raag. To download the source dataset that contains raw data values, go here: https://data.transportation.gov/dataset/Crossing-Inventory-Source-Data-Form-71-Current/xp92-5xme.1Licence not specifiedabout 2 years ago
- This dataset provides lane closure occurrences within the Texas Department of Transportation (TxDOT) highway system in a tabular format. A continuously updating archive of the TxDOT WZDx feed data can be found at ITS WorkZone Raw Data Sandbox and the ITS WorkZone Semi-Processed Data Sandbox. The live feed is currently compliant with the Work Zone Data Exchange (WZDx) Specification version 2.0.1Licence not specifiedabout 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains metadata about each data collection run. See also the instances table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/k74u-yqu6) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/uvrt-varj).1Licence not specifiedabout 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the car-following instances recorded by Volpe staff. See also the runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/285w-yjf5) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/uvrt-varj).1Licence not specifiedabout 2 years ago
- Available only on the web, provides information for airport pair markets rather than city pair markets. This table only lists airport markets where the origin or destination airport is an airport that has other commercial airports in the same city. Midway Airport (MDW) and O'Hare (ORD) are examples of this. All records are aggregated as directionless markets. The combination of Airport_1 and Airport_2 define the airport pair market. All traffic traveling in both directions is added together. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedabout 2 years ago
- This is list of data elements and their attributes that are used by data assets at the Federal Highway Administration.1Licence not specifiedabout 2 years ago
- The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 6 data collection runs, collected using an Instrumented Research Vehicle (IRV) along freeways and arterials in western Massachusetts in the summer of 2016 to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the car-following instances recorded by Volpe staff. See also the runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/b3k6-qwyh) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/4qbx-egtn).1Licence not specifiedabout 2 years ago
- About the Data: The dataset includes recall information related to specific NHTSA campaigns. Users can filter based on characteristics like manufacturer and component. The dataset can also be filtered by recall type: tires, vehicles, car seats, and equipment. The earliest campaign data is from 1966. The dataset displays the completion rate from the latest Recall Quarterly Report or Annual Report data from Year 2015 Quarter 1 (2015-1) onward. Data Reporting Requirement: Manufacturers who determine that a product or piece of original equipment either contains a safety defect or is not in compliance with Federal safety standards are required to notify NHTSA within 5 business days. NHTSA requires that manufacturers file a Defect and Noncompliance Report in compliance with Federal Regulation 49 (the National Traffic and Motor Safety Act) Part 573, which identifies the requirements for safety recalls. This information is stored in the NHTSA database referenced above. Notes: The default visualization depicted here represents only the top 12 manufacturers for the current calendar year. Please use the Filters for specific data requests. For a complete historical perspective, please visit: https://www.nhtsa.gov/sites/nhtsa.gov/files/2023-03/2022-Recalls-Annual-Report_030223-tag.pdf.1Licence not specifiedabout 2 years ago
- Analysis of the projects proposed by the seven finalists to USDOT's Smart City Challenge, including challenge addressed, proposed project category, and project description. The time reported for the speed profiles are between 2:00PM to 8:00PM in increments of 10 minutes.1Licence not specifiedabout 2 years ago
- 1Licence not specifiedover 2 years ago
- 1Licence not specifiedover 2 years ago
- The Federal Highway Administration (FHWA) has been receiving Highway inventory, usage, condition and performance data from State Departments of Transportation (DOT) since 1978 to support the program mission of the FHWA. Specifically, HPMS consists of detailed road segment data (63 Attributes) for higher order systems. Sample attributes for collector systems and summary data for the local roads. New requirements for HPMS took effect in 2014 that required each State DOTs to expand their Linear Referencing Systems (LRS), a statewide geospatial representation of their road system that includes all public roads. This requirement was put in place to support highway safety. States DOTs submit HPMS data annually to the FHWA following a prescribed format outlined in the Highway Performance Monitoring System Field Manual.1Licence not specifiedover 2 years ago
- This set of data files was acquired under USDOT FHWA cooperative agreement DTFH61-11-H-00025 as one of the four test data sets acquired by the USDOT Data Capture and Management program. This is the primary loop detector data table. It contains one-minute volume, occupancy, and data quality flags for the arterial loop detector data.1Licence not specifiedover 2 years ago
- Volume of gasoline reported by the States each month, based on reports from suppliers and distributors. These amounts are reported in various Office of Highway Policy Information (OHPI) products including the longstanding Monthly Motor Fuel Report, and the annual Highway Statistics publications.1Licence not specifiedover 2 years ago
- The data in this data environment was collected from the Pasadena, California testbed, namely I-210, SR 134, and nearby arterials. The source of these data is from the Caltrans – Performance Measurement System (PeMS). Speed data from this dataset were used to derive the freeway travel time. There are three separate text files with one for each operational condition.1Licence not specifiedover 2 years ago
- Contains all Basic Mobility Control Message (BMCMs) generated during the Advanced Messaging Concept Development (AMCD) field testing program. While there is no specific standard in existence that addresses the content of a BMCM, the following format was derived to control the configuration and content of BMMs requested from the vehicle. All BMCMs are generated by the VCC Cloud server and transmitted to OBU clients through either a DSRC or cellular communications channel.1Licence not specifiedover 2 years ago
- Data collected on the SS-30 form. Transit agencies report to the NTD security personnel in terms of Full-Time Equivalents (FTE) according to the staffing levels at the beginning of the year. One FTE typically works 40 hours per week. An agency may use any reasonable method to allocate personnel across modes, such as allocating based on modal ridership or on modal annual trips. In certain instances, agencies may base personnel numbers on the prior year’s total hours worked.1Licence not specifiedover 2 years ago
- This set of data files was acquired under USDOT FHWA cooperative agreement DTFH61-11-H-00025 as one of the four test data sets acquired by the USDOT Data Capture and Management program.The freeway data consists of two months of data (Sept 15 2011 through Nov 15 2011) from dual-loop detectors deployed in the main line and on-ramps of a Portland-area freeway. The section of I-205 NB covered by this test data set is 10.09 miles long and the section of I-205 SB covered by this test data set is 12.01 miles long The data includes: flow, occupancy, and speed.1Licence not specifiedover 2 years ago
- State DOTs will provide Local and Rural Minor Collector Mileage summarized by county, ownership, and Paved and Unpaved. This data is provided in a direct input by the State DOTs.1Licence not specifiedover 2 years ago
- Curated FRA Safety data pertaining to Rail Equipment Accidents (Form 54) Unique Train Accidents Please note that this dataset displays unique train accidents. When an accident involves multiple railroads, each railroad must report its data. As a result, there can be multiple records for one accident. This dataset has been modified to pull and display one record for each accident. Highway-rail crossing incidents have also been removed from this dataset because they are not considered train accidents. To see the full dataset with all reports with all data for all accidents, please visit https://data.transportation.gov/Railroads/Rail-Equipment-Accident-Incident-Data/85tf-25kj1Licence not specifiedover 2 years ago
- This dataset is the source dataset and contains raw data values. It will replace the current data download (https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/DownloadCrossingInventoryData.aspx) when the safetydata.fra.dot.gov site is decommissioned in 2024. To download data that contains data in a user-friendly human-readable format, please reference https://data.transportation.gov/Railroads/Crossing-Inventory-Data-Current/m2f8-22s6.1Licence not specifiedover 2 years ago
- This data set shows Amtrak industrial, office, and commercial real estate in opportunity zones1Licence not specifiedover 2 years ago
- 1Licence not specifiedover 2 years ago
- This represents the Service data reported to the NTD by transit agencies to the NTD. In versions of the data tables from before 2014, you can find data on service in the file called "Transit Operating Statistics: Service Supplied and Consumed." If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.1Licence not specifiedover 2 years ago
- Data set containing all of the Federal Funding Allocation inputs submitted by NTD reporting transit agencies from 2022 to the most recently published data within the Federal Transit Administration's NTD Data website.1Licence not specifiedover 2 years ago
- All Railroads covered by Part 225 Accident/Injury reporting are required to provide monthly summary statistics via the form F6180.55.1Licence not specifiedover 2 years ago
- Provides fare premiums for airports in the top 1,000 city pairs, and demonstrates the impact of low-fare service and hub domination on fare levels. All records are aggregated as directionless city pair markets. Air traffic in each direction is combined. https://www.transportation.gov/policy/aviation-policy/competition-data-analysis/research-reports1Licence not specifiedover 2 years ago
- The Highway Performance Monitoring System (HPMS) compiles data on highway network extent, use, condition, and performance. The system consists of a geospatially‐enabled database that is used to generate reports and provides tools for data analysis. Information from HPMS is used by many stakeholders across the US DOT, the Administration, Congress, and the transportation community.1Licence not specifiedover 2 years ago
- Contains all Basic Safety Messages (BSMs) collected during the Advanced Messaging Concept Development (AMCD) field testing program. For this project, all of the Part I BSM message fields were populated. Additional data fields were also added to the row to identify sender, time of communication, mode of communication, etc., allowing the consumer of this data set to accurately track messages through the system. All BSMs are generated by OBUs and ultimately received by the VCC Cloud server.1Licence not specifiedover 2 years ago
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