COVID-19 and Traffic Safety: Role of Infrastructure and Exposure

At the time of this writing, the COVID-19 pandemic continues to intensify, with 106,314,695 confirmed cases and 2,320,720 deaths spread across nearly every country on Earth. Early lockdowns largely kept people at home, thereby reducing traffic levels. Theoretically, reduced traffic exposure should result in reduced motor vehicle crashes. However, a variety of factors complicate this relationship. Empty streets provide increased opportunity for speeding and aggressive driving behavior. More consumption of alcohol and drugs during lockdowns could translate to more driving while intoxicated. Public transit trips have decreased by 85% in some cities, with many of these trips converting to less-safe personal vehicles. Similarly, higher levels of vulnerable road users on the streets may lead to worse safety outcomes. Emergency services were stretched thin, so enforcement and emergency response times to motor vehicle collisions may have decreased in some locations. The overall goal will be to understand how the COVID-19 pandemic has impacted travel behavior, collision frequencies, and collision severity. The research team has three initial hypotheses. First, overall decreases in traffic exposure have resulted in decreases in crash frequency but increases in crash severity. However, these increases in injuries and fatalities will not be distributed evenly. Therefore secondly, large and fast roadways and networks based on the functional classification system will have experienced worse safety outcomes while traditional networks with smaller roadways will have experienced improved outcomes. Third, the impacts of roadway design and networks will outweigh the impacts of other contributing factors or changes to exposure. This project will consist of three analyses. First, the team will perform a national analysis of motor vehicle fatalities using Fatality Analysis Reporting System data. The team will compare 2015-2019 fatalities to those that occurred in 2020. Limited variables are available on the national scale, but the team anticipates using FARS attributes (including drug/alcohol involvement, contributing factors, and travel mode), census data (including urban/rural, household income, and population density), and road networks (while the team can analyze network connectivity on the national level, the team will not be able to analyze speed limits or functional classification). The purpose of this national analysis is to identify variables of interest for the second and third models. The second analysis will focus on three states (to be determined based on national results and data availability). While the team will explore the same variables as before, the critical benefit of this analysis is that the team will also analyze non-fatal collision trends. This will inform them of whether collision frequencies and/or severities have changed. The team will also examine spatial clustering to guide site selection for the third analysis. The third analysis will analyze one local region. While the team will analyze the same variables as above, the critical benefit of the local analysis is that the team will incorporate exposure into the models. The team anticipates obtaining exposure data from aggregated cell phone data. The team will also incorporate detailed factors that would be difficult to account for on a larger scale such as roadway functional classification, posted speed limit, number of lanes, and land use. The team will identify collision hotspots and compare them to areas where collisions have not increased to understand which factors have contributed to traffic safety outcomes. Findings will be important in two regards. First, they may inform actions for future epidemics, pandemics, economic downturns, and natural disasters. For example, if the team finds that drug/alcohol involvement has increased, the team may be able to better prepare treatments for similar future events. Second, findings will reveal the intrinsic safety of street and network typologies. This body of research has developed significantly over recent decades and findings will provide important contributions to the body of knowledge, providing benefits even outside of pandemics.

• Record URL:
  https://transet.lsu.edu/wp-content/uploads/sites/16/2021/08/21SAUNM02.pdf
• Supplemental Notes:
  • 21SAUNM02

Language

• English

Project

• Status: Active
• Funding: $100000
• Contract Numbers:

  69A3551747106

• 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:

  Transportation Consortium of South-Central States (Tran-SET)

  Louisiana State University
  Baton Rouge, LA  United States  70803
• Project Managers:

  Mousa, Momen

• Performing Organizations:

  University of New Mexico, Albuquerque

  Department of Civil Engineering
  Albuquerque, NM  United States  87131-0001
• Principal Investigators:

  Ferenchak, Nicholas

• Start Date: 20210801
• Expected Completion Date: 20230201
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: COVID-19; Crash rates; Crash severity; High risk locations; Traffic safety
• Identifier Terms: Fatality Analysis Reporting System (FARS)
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01833041
• Record Type: Research project
• Source Agency: Transportation Consortium of South-Central States (Tran-SET)
• Contract Numbers: 69A3551747106
• Files: UTC, RIP
• Created Date: Jan 20 2022 2:38PM