Assessing the Effectiveness of Connected Vehicle Technologies based on Driving Simulator Experiments

Connected vehicle technology is expected to reduce crashes and improve roadway safety overall despite its effect being dependent on the content of crash scenarios. The reason behind this is that the heterogeneity between crash scenarios may cause variation in a driver’s perception and interpretation of the crash scenarios. Further, the heterogeneity may lead to different driver behaviors and evasive strategies. Consequently, both the benefits and influence of connected vehicle technology are affected. This project aimed to identify the variation of the performance of connected vehicle technology between different crash scenarios. Specifically, two types of connected vehicle technologies, forward collision warning (FCW) technology and pedestrian-to-vehicle (P2V) technology, were tested in four rear-end crash scenarios and three pedestrian crash scenarios, respectively. The results showed promising effectiveness of FCW and P2V technologies to reduce the possibility of a crash. Specifically, FCW reduced rear-end crashes by 56.6%-69.8%, and P2V reduced pedestrian crashes by 89.2%-97.2%. More importantly, the results captured a significant variation in the performance of FCW and P2V between crash scenarios. In different scenarios, the technologies aroused different driver brake operations, and, consequently, the technologies achieved different safety benefits. In addition, the interaction effects between technologies and driver features were affected by crash scenarios. Age, gender, crash/citation experience, and driving experience were found to affect the warning effect in different scenarios. This study has practical implications for the understanding of how heterogeneity of crash scenarios can affect connected vehicle technology.

• Dataset URL:
  https://doi.org/10.7910/DVN/XU6HOA
• Record URL:
  http://safersim.nads-sc.uiowa.edu/final_reports/UCF%202%20Y2_Report.pdf
• 
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/56077
• Dataset URL:
  https://rosap.ntl.bts.gov/view/dot/56618
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program. Supporting datasets available at: https://doi.org/10.7910/DVN/XU6HOA
• Corporate Authors:

  University of Central Florida, Orlando

  Department of Civil, Environmental and Construction Engineering
  Orlando, FL  United States  32816

  Safety Research Using Simulation University Transportation Center (SaferSim)

  University of Iowa
  Iowa City, IA  United States  52242

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Wu, Yina
  • 0000-0001-6516-8144
  • Yue, Lishengsa
  • 0000-0002-0864-0075
  • Abdel-Aty, Mohamed
  • 0000-0002-4838-1573
• Publication Date: 2019-12

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; Photos; References; Tables;
• Pagination: 67p

Subject/Index Terms

• TRT Terms: Braking; Connected vehicles; Crash avoidance systems; Drivers; Driving simulators; Evaluation and assessment; Pedestrian vehicle crashes; Rear end crashes; Warning systems
• Subject Areas: Highways; Pedestrians and Bicyclists; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01736330
• Record Type: Publication
• Contract Numbers: 69A3551747131
• Files: UTC, NTL, TRIS, ATRI, USDOT
• Created Date: Apr 20 2020 10:52AM