Analyzing Rear-End Collision Risk Relevant to Autonomous Vehicles by Using a Humanlike Brake Model-Reference-Cited by-同舟云学术

Analyzing Rear-End Collision Risk Relevant to Autonomous Vehicles by Using a Humanlike Brake Model

Published:2024-07 Issue:7 Volume:150 Page:
ISSN:2473-2907
Container-title:Journal of Transportation Engineering, Part A: Systems
language:en
Short-container-title:J. Transp. Eng., Part A: Systems

Author:

Liang Ci¹^ORCID,Ghazel Mohamed²^ORCID,Ci Yusheng³^ORCID,Zheng Wei⁴

Affiliation:

1. Associate Professor, School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China. ORCID: .

2. Research Director, Division Assessment of Automated Transportation Systems and Safety (ESTAS), Université Gustave Eiffel, Campus de Lille, Lille 100044, France. ORCID: .

3. Associate Professor, School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China (corresponding author). ORCID: .

4. Professor, Collaborative Innovation Center of Railway Traffic Safety, and School of Automation and Intelligence, Beijing Jiaotong Univ., Beijing 100044, China.

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JTEPBS.TEENG-8250

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4. BICMI (Beijing Innovation Center for Mobility Intelligent). 2023. “Beijing autonomous vehicle road test report.” Accessed March 16 2023. http://www.mzone.site/.

5. Chen J. R. She S. Yang and J. Ma. 2023. “The city scale effect and the Baidu index prediction model of public perceptions of the risks associated with autonomous driving technology.” In Proc. Int. Conf. on Human-Computer Interaction 425–441. Cham: Springer.

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