Impact of Urban Transportation Infrastructure and Motorist Behavior on Motorcycle Crashes

The Fatality Analysis Reporting System database shows that, in stark contrast to the 34- percent decline in non-motorcyclist crash–related fatalities, motorcyclist crash–related fatalities were up 86 percent with only three year-to-year declines since 1997, while non-motorcyclist crash–related fatalities had 13 year-to-year declines since 1997. At the national level, the rate of motorcyclist fatalities per vehicle mile traveled is 29 times higher than the rate among passenger car occupants, with overall injury rates approximately five times higher among motorcyclists than passenger car occupants. Given the frequency of motorcycle crashes and their staggering toll in terms of loss of life and economic costs across Region 6, there is an urgent need to continue to work diligently toward driving the frequency of these crashes toward zero. The purpose of this research is to perform a comprehensive evaluation of crash and operational data to understand the complex nature of motorcycle crashes in Texas through construction of a motorcycle crash database and a multi-year analysis of these data in with an emphasis on the prevention of fatal and incapacitating injury crashes in Region 6. This includes compilation of motorcycle crash reports in the target area, calculation of crash counts and rates, and identifying road segments and intersections with highly concentrated motorcycle 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 motorcyclists, and road users behaviors as well as the common characteristics of the built environment that contribute to unsafe actions and conditions. The outcomes of such analysis can be actionable measures to reduce fatalities and injuries resulting from crashes that involve motorcycles and to develop regional and state mitigation targets. Moreover, the economic downturn resulting from COVID-19 pandemic led to a significant drop in travel demand and motorcyclist/driver’s exposure to collisions but studies suggested that it had a differential impact on different road users. For example, research on previous economic recessions suggests that these conditions affect the mental wellbeing of people and consequently their behavior on the road. COVID-19 pandemic effects in terms of motorists’ behavior, the unusually lower traffic volumes, and road safety in general are currently unknown, as the unprecedented nature and severity of this pandemic do not resemble anything seen before. Several research questions may arise on the potential motorcyclist/driver- and environment-related factors associated with COVID-19 pandemic that may affect traffic safety during and well after the pandemic. This study will also include an in-depth analysis aiming at pinpointing variables that may have affected road safety involving motorcycles during the pandemic. In order to provide an efficient and quick solution to the problem, the research team aims to carry out the tasks outlined below: 1. The research team will first undertake a thorough review of published literature on motorcycle safety countermeasures, a review of Intelligent Transportation System (ITS) and other advanced technologies for motorcycles and other vehicles, an analysis of motorcycle crash and injury data, and a statewide survey of transportation officials. Available past research and reports of a related nature, from Texas, Region 6, across the nation, and internationally, will be reviewed. 2. The research team will compile operational and safety data from sources such as the Texas Crash Records Information System (CRIS), the national Fatality Analysis and Reporting System (FARS), which has far more specialized detail on motorcycle crashes, Texas Department of State Health Services records, and crash narratives as well as site visits. 3. The research team will use data mining to examine space-time indicators that may reveal information about the correlation between motorcycle crashes and traffic volumes, common characteristics of the built environment that contribute to unsafe actions and conditions, and other factors. 4. The research 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. 5. The research team will employ three categories of statistical analytical approaches: descriptive measures, analytical statistics produced by statistical models, and geospatial plotting and related measures.

• Supplemental Notes:
  • 22SAUTSA66

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 Texas at San Antonio

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

  Sharif, Hatim

• Start Date: 20220401
• Expected Completion Date: 0
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Built environment; COVID-19; Crash causes; Crash data; Data analysis; Motorcycle crashes
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01844946
• Record Type: Research project
• Source Agency: Transportation Consortium of South-Central States (Tran-SET)
• Contract Numbers: 69A3551747106
• Files: UTC, RIP
• Created Date: May 9 2022 6:09AM