Investigating safety and liability of autonomous vehicles: Bayesian random parameter ordered probit model analysis

Investigating safety and liability of autonomous vehicles: Bayesian random parameter ordered probit model analysis

Purpose – This study aims to investigate the safety and liability of autonomous vehicles (AVs), and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs. Design/methodology/approach – The actual crash data were obtained from California D...

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Bibliographic Details
Main Authors: Quan Yuan, Xuecai Xu, Tao Wang, Yuzhi Chen
Format: Article
Language:English
Published: Tsinghua University Press 2022-10-01
Series:Journal of Intelligent and Connected Vehicles
Subjects:
safety
bayesian random parameter ordered probit model
liability
autonomous vehicles
advanced vehicle safety systems
Online Access:https://www.emerald.com/insight/content/doi/10.1108/JICV-04-2022-0012/full/pdf?title=investigating-safety-and-liability-of-autonomous-vehicles-bayesian-random-parameter-ordered-probit-model-analysis

Internet

https://www.emerald.com/insight/content/doi/10.1108/JICV-04-2022-0012/full/pdf?title=investigating-safety-and-liability-of-autonomous-vehicles-bayesian-random-parameter-ordered-probit-model-analysis

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