L o a d i n g
Overviewintelligent-transportation-systems-itsits-joint-program-office-jpospeed-datatraffic-detectorstraffic-flowtravel-timework-zones
Data for Artificial Intelligence: Data-Centric AI for Transportation: Work Zone Use Case proposes a data integration pipeline that enhances the utilization of work zone and traffic data from diversified platforms and introduces a novel deep learning model to predict the traffic speed and traffic collision likelihood during planned work zone events. This dataset is raw Maryland roadway incident data without rows where road_tmc and road are inconsistent.
Additional Information
KeyValue
Common-Core_Bureau-Code021:15
Common-Core_Contact-Emailelina.zlotchenko@dot.gov
Common-Core_Contact-NameElina Zlotchenko
Common-Core_Geographic-CoverageMaryland highway network
Common-Core_Licensehttp://www.usa.gov/publicdomain/label/1.0/
Common-Core_Program-Code021:042
Common-Core_Public-Access-Levelpublic
Common-Core_PublisherFederal Highway Administration
categories{}
owner_display_nameITS-JPO
source_created_at2024-09-16T19:26:10.000Z
source_updated_at2024-11-20T17:53:36.000Z
harvest_object_id416c8cd5-4ec5-4a74-898a-b368422be91b
harvest_source_ida7dcdbaf-e4e3-4821-be64-d4ab014fcc67
harvest_source_titleDOT Open Data Catalog
Files
- CSVData for Artificial Intelligence: Data-Centric AI for Transportation: Work Zone Use Case Raw Maryland Incidents Matched