An Improved Lane-Changing Model for Connected Automated Vehicles under Cyberattacks

Existing studies focus on surveying cyberattacks and evaluating their impacts on vehicular longitudinal behaviors on a single lane. This paper investigates the effects of cyberattacks on vehicular lateral behaviors on a two-lane highway, i.e., the lane-changing behaviors under cyberattacks. The lane change is a complex maneuver, which requires integrating neighbor vehicles’ dynamical parameters such as velocity, position and/or acceleration. This study introduces a car-following model to derive vehicles’ dynamical parameters. Specifically, this study adopts the Intelligent Driver Model (IDM) to characterize the car-following movements. Then, incorporating a classical lane-changing model, i.e., minimizing overall braking induced by lane changes (MOBIL) model, this study proposes an extended lane-changing model with cyberattacks to obtain the decision-making conditions. Finally, simulations are conducted to illustrate the impact of different malicious attacks such as falsified acceleration, speed, and position on vehicles’ movements. These results demonstrate that cyberattacks could cause traffic congestion, low traffic efficiency, and collisions.

• Record URL:
  https://doi.org/10.1061/9780784484265.141
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784484265
• Supplemental Notes:
  • © 2022 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • He, Shan
  • Zhang, Shaowei
  • Chen, Hengwei
  • Wang, Pengcheng
• Conference:
  • 22nd COTA International Conference of Transportation Professionals
  • Location: Changsha Hunan Province, China
  • Date: 2022-7-8 to 2022-7-11
• Publication Date: 2022

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 1503-1512
• Monograph Title: CICTP 2022: Intelligent, Green, and Connected Transportation

Subject/Index Terms

• TRT Terms: Car following; Computer security; Connected vehicles; Lane changing
• Identifier Terms: Intelligent Driver Model (IDM)
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Security and Emergencies;

Filing Info

• Accession Number: 01864103
• Record Type: Publication
• ISBN: 9780784484265
• Files: TRIS, ASCE
• Created Date: Nov 17 2022 10:15AM