A review of scenario cases for autonomous transportation system: Insights from CAV safety testing and scenario generation

Zhang Y 1 , Shi X 2 , Shao Y 1 , Shiwakoti N 3 , Zhang J 1 , Pu Z 4 Show all authors , Ye Z 5

Affiliations 

  • 1 Jiangsu Key Laboratory of Urban ITS, Southeast University, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, China; School of Transportation, Southeast University, 2 Dongnandaxue Rd, Nanjing, Jiangsu 211189, China
  • 2 Jiangsu Key Laboratory of Urban ITS, Southeast University, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, China; School of Transportation, Southeast University, 2 Dongnandaxue Rd, Nanjing, Jiangsu 211189, China. Electronic address: shixiaomeng@seu.edu.cn
  • 3 School of Engineering, RMIT University, Carlton, Victoria 3053, Australia
  • 4 Jiangsu Key Laboratory of Urban ITS, Southeast University, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, China; School of Transportation, Southeast University, 2 Dongnandaxue Rd, Nanjing, Jiangsu 211189, China; School of Engineering and Advanced Engineering Platform, Monash University, Jalan Lagoon Selatan, 47500 Bandar Sunway, Malaysia
  • 5 Jiangsu Key Laboratory of Urban ITS, Southeast University, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, China; School of Transportation, Southeast University, 2 Dongnandaxue Rd, Nanjing, Jiangsu 211189, China. Electronic address: yezhirui@seu.edu.cn
Accid Anal Prev, 2025 Mar 11;215:107994.
PMID: 40073462 DOI: 10.1016/j.aap.2025.107994

Abstract

Ensuring the reliability and trustworthiness of connected and automated vehicle (CAV) technologies is crucial before their widespread implementation. Instead of focusing solely on the automation levels of individual vehicles, it is essential to consider the autonomous operations of the entire autonomous transportation system (ATS) to achieve automated traffic. However, designing and generating scenarios that unify the diverse properties of CAV testing and establish mutual trust among stakeholders pose significant challenges. Previous studies have predominantly focused on the automation levels of CAVs when characterizing scenarios, neglecting the autonomous level of the entire scenario from an ATS perspective. Moreover, there remains research potential in evaluating whether the testing scenario libraries can be effectively integrated into the CAV testing process. In this paper, we propose a grading framework for traffic scenarios based on autonomous levels in the ATS. We also classify and summarize the traffic scenarios used in CAV safety testing. Through a comprehensive literature review, we identify prevailing issues and patterns in scenario design and provide insights and directions for future research in this field.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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