Impact of Truck Drivers and Transportation Infrastructure Characteristics on Large Truck Crashes

For the past three decades, Texas has had the highest number of fatal crashes involving large trucks in the United States. Other states in Regions 6 also have high rates of large truck crashes. Due to the size and weight of large trucks, their crashes usually are very destructive. Although large trucks have a significant impact on traffic safety in Region 6, very little analysis has been conducted on the risk factors associated with crashes involving large trucks, especially the roadway-related risk factors. The purpose of this research is to perform a comprehensive evaluation of crash and operational data to identify the root causes of crashes involving large trucks in Texas. This includes developments of a database of large truck crash reports in the target area, calculation of crash counts and rates, and identifying road segments and intersections with highly concentrated large truck crashes and the unsafe actions that are contributing to such crashes. The crash data analysis will include detailed review of the crash narratives and diagrams as part of the crash database building process to help elucidate the true causes of the crashes. The evaluation will include operational and physical characteristics of the crash locations, severity of injuries, environmental conditions, characteristics of truck drivers, and road users behaviors as well as the common characteristics of the built environment that contribute to unsafe actions and conditions. The above evaluation shall allow the research team to identify on-system and off-system segments and intersections with highly concentrated large truck crashes and the unsafe actions that are contributing to these crashes and provide safety countermeasures and recommendations for further study. The changes in crashes in 2020 could primarily be attributed to changes in travel due to COVID-19. The COVID-10 impact could also be highly variable based on location, and it might be difficult to determine if these changes were due to COVID-19, other factors, or just simple randomness associated with highly random and independently distributed events such as large truck crashes. However, the team carefully examines the 2020 crash data to see if there would be any consistent identifiable impacts of COVID-19. This research will also include an in-depth analysis aiming at pinpointing variables that may have affected road safety associated with large trucks during the pandemic. In order to provide an efficient and quick solution to the problem, the team aims to carry out the tasks outlined below: (1) The team will first undertake a thorough review of the available literature. Available past research and reports of a related nature, from Texas, Region 6, across the nation, and internationally, will be reviewed. Some of these resources will be listed and individually described elsewhere in this proposal. A major focus of the research team will be identification and prioritizing of risk factors associated with crashes involving large trucks and the effectiveness of engineering/educational countermeasures to improve safety. (2) The team will download operational and safety data from sources such as Crash Records Information System (CRIS), the Fatality Analysis and Reporting System (FARS), which has far more specialized detail on large truck crashes, Texas Department of State Health Services records, and crash narratives as well as site visits. (3) The team will use data mining to examine spatio-temporal indicators that may reveal information about the correlation between crash numbers and traffic volumes, common characteristics of the built environment that contribute to unsafe actions and conditions, and other factors. (4) The team will use different data collection techniques to understand road user’s behavior and review crash narratives and diagrams. These observations will not only be helpful in the analysis of risk factors, but also provide a framework that guides decision-making throughout the entire process, from identifying a problem to implementing a countermeasure.

Language

  • English

Project

  • Status: Active
  • Funding: $90000
  • 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 Texas at San Antonio

    One UTSA Circle
    San Antonio, TX  United States  78249
  • Principal Investigators:

    Sharif, Hatim

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

Subject/Index Terms

Filing Info

  • Accession Number: 01833044
  • Record Type: Research project
  • Source Agency: Transportation Consortium of South-Central States (Tran-SET)
  • Contract Numbers: 69A3551747106
  • Files: UTC, RIP
  • Created Date: Jan 19 2022 4:12PM