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.

• Record URL:
  https://www.mountain-plains.org/research/details.php?id=554

Language

• English

Project

• Status: Completed
• Funding: $337686
• Contract Numbers:

  69A3551747108

• 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:

  Mountain-Plains Consortium

  North Dakota State University
  Fargo, ND  United States  58108
• Project Managers:

  Tolliver, Denver

• Performing Organizations:

  Upper Great Plains Transportation Institute

  North Dakota State University
  1320 Albrecht Boulevard
  Fargo, ND  United States  581052

  Dept. 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: 20240731
• Actual Completion Date: 20230923
• 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: Jul 1 2021 5:05PM