Investigating safety and liability of autonomous vehicles: Bayesian random parameter ordered probit model analysis
نویسندگان
چکیده
Purpose This study aims to investigate the safety and liability of autonomous vehicles (AVs), identify contributing factors quantitatively so as provide potential insights on AVs. Design/methodology/approach The actual crash data were obtained from California DMV Sohu websites involved in collisions AVs 2015 2021 with 210 observations. Bayesian random parameter ordered probit model was proposed reflect AVs, respectively, well accommodating heterogeneity issue simultaneously. Findings findings show that day, location type significant injury severity while reason influencing liability. Originality/value results meaningful countermeasures support policymakers or practitioners making strategies regulations about AV
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ژورنال
عنوان ژورنال: Journal of intelligent and connected vehicles
سال: 2022
ISSN: ['2399-9802']
DOI: https://doi.org/10.1108/jicv-04-2022-0012