Incorporating Psychographic Factors to Assess the Impact of Cybersecurity Breaches on Connected and Automated Vehicles and Road Safety

Connected and automated vehicles (CAVs) promise safer, more efficient travel and present complex challenges. This research proposes a framework for integrating CAVs into diverse road environments, examining safety, security, and public acceptance. It uses publicly available data to develop a standardized safety model that considers infrastructure readiness, socioeconomic factors, and behavioral responses to ensure smooth coexistence with conventional vehicles and vulnerable users. Cybersecurity is a central focus, prompting robust strategies to safeguard against emerging threats. A case study illustrates how system security concerns can deter autonomous vehicle adoption, employing Conditional Average Treatment Effects (CATE) via Generalized Random Forests (GRF). Findings show that security worries disproportionately affect certain subgroups, underscoring the need for tailored policies. By blending theoretical insights with empirical evidence, this study offers a scalable roadmap to ensure safe, equitable, and publicly trusted CAV deployment.

• Record URL:
  • https://uh.edu/cybercare/research/projects/c23c02/
• 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: $60,000.00
• 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

• Performing Organizations:

  University of Houston, Texas

  Houston, TX  United States 

  Rice University

  Houston, Texas  United States 
• Principal Investigators:

  Wang, Kailai

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

Subject/Index Terms

• TRT Terms: Acceptance; Autonomous vehicles; Computer security; Connected vehicles; Traffic safety
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01954311
• 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: May 5 2025 4:14PM