A matched case-control method to model car-following safety

Car-following safety is related to both observed driving characteristics (e.g. car-following behaviour) and unobserved driver heterogeneity (e.g. drivers’ psychological features). Two major issues remain in the existing literature, i.e. limiting to longitudinal characteristics and not addressing the confounding effects of unobserved driver heterogeneity. This study takes a matched case–control approach to model car-following safety with both longitudinal and lateral driving characteristics. Unobserved driver heterogeneity is controlled by matching preceding and following vehicle IDs. Results show that unstable lateral movements of preceding vehicles and following vehicles contribute to higher crash risks. Comparison results on two datasets with different congestion levels reveal that it is safer in more congested traffic when the following vehicle maintains more stable longitudinal and lateral behaviours, and greater speed difference, headway, and spacing regarding its preceding vehicle. This study provides insights in enhancing roadway safety management and benefiting the automated vehicle development by warnings on associated risks.

• Record URL:
  • https://doi.org/10.1080/23249935.2022.2055198
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23249935
• Supplemental Notes:
  • © 2022 Hong Kong Society for Transportation Studies Limited. Abstract reprinted with permission of Taylor & Francis.
• Authors:
  • Li, Qianwen
  • Yao, Handong
  • Li, Xiaopeng
• Publication Date: 2023-5

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References;
• Pagination: 2055198
• Serial:
  • Transportmetrica A: Transport Science
  • Volume: 19
  • Issue Number: 3
  • Publisher: Taylor & Francis
  • ISSN: 2324-9935
  • EISSN: 2324-9943
  • Serial URL: http://www.tandfonline.com/loi/ttra21

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Car following; Driving behavior; Highway safety; Traffic congestion; Traffic distribution
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Safety and Human Factors;

Filing Info

• Accession Number: 01897205
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 23 2023 4:52PM