Understand Vehicle-Driver Complex Behaviors under Cyberattacks and Model the Consequences to the Urban Traffic System

Vehicle-to-infrastructure communication improves traffic safety and efficiency, but increasing connectivity also raises cybersecurity risks. Cyberattacks on intelligent transportation systems can manipulate data, leading to unsafe driving behaviors. This project investigates how cyberattacks impact driver behavior and safety using a driving simulator experiment with 32 participants of different ages, experiences, and genders. Participants drove through connected intersections under both benchmark and cyberattack conditions. Safety was assessed using the Surrogate Safety Assessment Model (SSAM), focusing on Proportion of Stopping Distance (PSD) and Time to Collision (TTC). Findings show that cyberattacks significantly threaten traffic safety, influencing speed, deceleration, and collision risks. Higher speeds at the end of a signal countdown increase the likelihood of pedestrian and right-angle collisions but reduce rear-end collision risk. Experienced drivers respond better to cyberattacks, with lower pedestrian and right-angle collision hazards than inexperienced drivers. No major differences were observed between male and female drivers under cyberattacks, though mixed effects of males and cyberattacks brings a higher rear-end collision risks than female in benchmark conditions. Speed mediates these effects, as experienced drivers decelerate more quickly, reducing frontal collision risks. This study highlights the dangers of cyberattacks in transportation and how human factors influence safety. The findings can help improve traffic management, driver education, and predictive safety models to reduce risks in connected vehicle environments.

• Record URL:
  • https://uh.edu/cybercare/research/projects/c23c16/
• Supplemental Notes:
  • This material is based on work supported by the U.S. Department of Transportation, OST-R, University Transportation Center Program, the USDOT Tier 1 UTC Transportation Cybersecurity Center for Advanced Research and Education (CYBER-CARE).

Language

• English

Project

• Status: Active
• Funding: $75,000.00
• Contract Numbers:

  69A3552348332

• 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 Cybersecurity Center for Advanced Research and Education (CYBER-CARE)

  University of Houston
  Houston, TX  United States 
• Project Managers:

  Zhang, Yunpeng

  Kline, Robin

• Performing Organizations:

  University of Cincinatti

  Cincinatti, OH  United States  45221
• Principal Investigators:

  Li, Zhixia

• Start Date: 20230701
• Expected Completion Date: 20260630
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Behavior; Computer security; Connected vehicles; Crash risk forecasting; Drivers; Driving simulators; Signalized intersections; Urban areas; Vehicle to infrastructure communications
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Safety and Human Factors; Security and Emergencies; Vehicles and Equipment;

Filing Info

• Accession Number: 01953956
• Record Type: Research project
• Source Agency: Transportation Cybersecurity Center for Advanced Research and Education (CYBER-CARE)
• Contract Numbers: 69A3552348332
• Files: UTC, RIP, STATEDOT
• Created Date: Apr 30 2025 4:04PM