Knowledge-Based Machine Learning for Freeway COVID-19 Traffic Impact Analysis and Traffic Incident Management [Research Brief]

Lu, Pan; Yang, Xianfeng (Terry); Gong, Yaobang; Isom, Tanner; Wang, Aaron

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Knowledge-Based Machine Learning for Freeway COVID-19 Traffic Impact Analysis and Traffic Incident Management [Research Brief]

2023-08-01
By Lu, Pan ; Yang, Xianfeng (Terry) ; Gong, Yaobang ; ...

File Language:

English

Details

Creators:

Lu, Pan ; Yang, Xianfeng (Terry) ; Gong, Yaobang ; Isom, Tanner ; Wang, Aaron
Corporate Creators:

North Dakota State University ; University of Utah ; Mountain-Plains Consortium
Corporate Contributors:

Upper Great Plains Transportation Institute ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology ; United States. Department of Transportation. University Transportation Centers (UTC) Program
Subject/TRT Terms:

COVID-19 Demand Freeways Incident Management Machine Learning Predictive Models Traffic Incidents Traffic Models Traffic Volume Travel Patterns
Publication/ Report Number:

MPC-23-502
Resource Type:

Brief
Geographical Coverage:

Utah;United States
Edition:

Research Brief
Corporate Publisher:

Mountain-Plains Consortium
Abstract:

Researchers examined the impacts of COVID-19 on traffic safety in three different stages to better understand the relationship between traffic demand patterns, daily confirmed cases/deaths, state policies, and public perceptions and other factors.
Format:

PDF
Funding:

MPC-657
Collection(s):

University Transportation Centers
Main Document Checksum:

urn:sha-512:013d1ed4aebf92568b1532afd0caa114db84da278c24f286720394cfc032648de69ec9beedf6d50a5951b2f877a918f2a12f57331e247d6973924003876ff085
Download URL:

https://rosap.ntl.bts.gov/view/dot/71877/dot_71877_DS1.pdf
File Type:

[PDF - 437.46 KB ]

File Language:

English

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