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A comprehensive assessment of connected and automated vehicle analytical, modeling, and simulation tools

Author

Listed:
  • Long, Keke
  • Ma, Ke
  • Li, Qianwen
  • Li, Xiaopeng
  • Huang, Zhitong
  • James, Rachel
  • Ghiasi, Amir

Abstract

Connected and Automated Vehicles (CAVs) promise to redefine the future of transportation. Infrastructure Owners and Operators (IOOs require advanced analytical, modeling, and simulation (AMS) tools) to grasp the impact of CAVs on their strategic goals, such as improving safety, enhancing mobility, and advancing equity, and assess policy modifications to steer the deployment of this technology effectively. Although recent research has made strides in developing models that characterize CAV behavior in mixed-traffic scenarios, significant modeling gaps persist. These gaps hinder decision-makers and policymakers from fully understanding how CAVs can serve as an instrumental force in driving desired improvements in transportation system performance. This study aims to identify these gaps by organizing two stakeholder webinars that focus on CAV AMS tools. The discussions from these webinars are categorized into three primary areas: CAV technologies, road user behaviors, and system-level modeling. This categorization helps structure an in-depth literature review designed to pinpoint existing shortcomings in CAV research. The study also provides an overview of current datasets that are both representative and capable of addressing some of these research gaps. Ultimately, this study seeks to act as a valuable reference for directing future research efforts in CAVs.

Suggested Citation

  • Long, Keke & Ma, Ke & Li, Qianwen & Li, Xiaopeng & Huang, Zhitong & James, Rachel & Ghiasi, Amir, 2025. "A comprehensive assessment of connected and automated vehicle analytical, modeling, and simulation tools," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:transe:v:196:y:2025:i:c:s1366554525000481
    DOI: 10.1016/j.tre.2025.104007
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