Analysis of Crashes Involving Pedestrians Across the United States: Implications for Connected and Automated Vehicles

This study explores how vulnerable road users, especially pedestrians, can be protected as connected and automated vehicles (CAVs) diffuse through the transportation system. Vehicle-to-pedestrian connectivity has the potential to enhance safety by reducing driver and pedestrian errors that result in crashes. To understand the nature of errors contributing to severe crashes, this study analyzes single vehicle-pedestrian fatal crashes, for which there is valuable detailed data available for analysis. To unlock the safety potential of CAVs, it is important to understand the behaviors of drivers and pedestrians prior to such crashes. This study investigates both driver and pedestrian pre-crash behaviors and their relationship to crash frequency, using data aggregated at the county level across the United States using Fatality Analysis Reporting System (FARS) crash data collected between 2013 and 2015 (N= 12,217 single vehicle-pedestrian fatal crashes). Because crash frequency is a count measure, Poisson regression and Geographically Weighted Poisson Regression (GWPR) models are estimated to analyze national FARS data. The results show that pedestrian pre-crash errors contribute substantially to fatal crashes (80%). Prevalent pedestrian pre-crash behaviors include dash/dart out, failure to yield right-of-way, improper use of roadway (standing, lying, walking), inattention (talking and eating), improper crossing (jaywalking) and invisibility (dark clothing, no light). A key issue to be addressed is the extent to which CAVs that automatically brake to avoid striking pedestrians or provide alerts and early warnings to both drivers and pedestrians may potentially prevent vehicle-pedestrian crashes. The analytical results provide insights regarding the potential of technology to improve safety.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ANF10 Standing Committee on Pedestrians.
• Authors:
  • Zhang, Meng
  • Khattak, Asad J
  • Shay, Elizabeth
• Conference:
  • Transportation Research Board 97th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2018-1-7 to 2018-1-11
• Date: 2018

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Maps; References;
• Pagination: 5p

Subject/Index Terms

• TRT Terms: Behavior; Connected vehicles; Crash analysis; Crash data; Crash rates; Drivers; Intelligent vehicles; Pedestrian safety; Pedestrian vehicle crashes; Pedestrians; Vulnerable road users
• Geographic Terms: United States
• Subject Areas: Data and Information Technology; Highways; Pedestrians and Bicyclists; Planning and Forecasting; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01657515
• Record Type: Publication
• Report/Paper Numbers: 18-04721
• Files: TRIS, TRB, ATRI
• Created Date: Jan 24 2018 9:25AM