Knowledge-Based Machine Learning for Freeway COVID-19 Traffic Impact Analysis and Traffic Incident Management
The U.S. Department of Transportation needs to quick response and adapt to the coronavirus (COVID-19) to ensure continuation of critical infrastructure support and relief for the American people. The COVID-19 has placed significant impacts to the traffic across the U.S. It is clear to see that traffic pattern, traffic demands, and duration alter with COVID status. Therefore, there is a critical research needs of studying the impact of COVID on traffic patterns and analyzing the relationship among traffic demand patterns, daily confirmed cases/death, state policies, public perception, etc. An effective model, based on the principle of newly invented knowledge-based machine learning, will be developed to predict the traffic impact of traffic incidents and advance traffic incident management (TIM) considering long-term impact of COVID on traffic.
Language
- English
Project
- Status: Active
- Funding: $337686
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Contract Numbers:
69A3551747108
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
North Dakota State University
Fargo, ND United States 58108 -
Project Managers:
Tolliver, Denver
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Performing Organizations:
Upper Great Plains Transportation Institute
North Dakota State University
Fargo, ND United StatesDept. of Civil and Environmental Engineering
University of Utah
Salt Lake City, UT United States -
Principal Investigators:
Lu, Pan
Yang, Xianfeng
- Start Date: 20210624
- Expected Completion Date: 20220731
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
- Source Data: MPC-657
Subject/Index Terms
- TRT Terms: COVID-19; Demand; Freeways; Incident management; Machine learning; Predictive models; Traffic incidents; Traffic models; Traffic volume; Travel patterns
- Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Security and Emergencies;
Filing Info
- Accession Number: 01775904
- Record Type: Research project
- Source Agency: Mountain-Plains Consortium
- Contract Numbers: 69A3551747108
- Files: UTC, RIP
- Created Date: Jun 30 2021 12:08PM