Crash comparison of autonomous and conventional vehicles using pre-crash scenario typology.

Liu, Qian; Wang, Xuesong; Wu, Xiangbin; Glaser, Yi; He, Linjia

Liu, Qian; Wang, Xuesong; Wu, Xiangbin; Glaser, Yi; He, Linjia.

Afiliação

Liu Q; College of Transportation Engineering, Tongji University, Shanghai 201804, China; The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Shanghai 201804, China.
Wang X; College of Transportation Engineering, Tongji University, Shanghai 201804, China; The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Shanghai 201804, China; National Engineering Laboratory for Integrated Optimization of Road Traffic and Safety Analysis Technologies, 88 Qianro
Wu X; Intelligent Driving Lab, Intel Labs China, No. 2 South Kexueyuan Road, Beijing 100190, China.
Glaser Y; Global Safety Center, GM, Warren, MI 48092-2031, USA.
He L; College of Transportation Engineering, Tongji University, Shanghai 201804, China; The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Shanghai 201804, China.

Accid Anal Prev ; 159: 106281, 2021 Sep.

Article em En | MEDLINE | ID: mdl-34273622

Assuntos

Acidentes de Trânsito; Condução de Veículo; Bases de Dados Factuais; Humanos; Tempo de Reação; Meios de Transporte; Estados Unidos

Palavras-chave

Automated driving system; Autonomous vehicle; Conventional vehicle; In-depth crash investigation; Perception-reaction time; Pre-crash scenario typology

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Condução de Veículo / Acidentes de Trânsito Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Accid Anal Prev Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China

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