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.

Afiliación

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 en En | MEDLINE | ID: mdl-34273622

Asunto(s)

Accidentes de Tránsito; Conducción de Automóvil; Bases de Datos Factuales; Humanos; Tiempo de Reacción; Transportes; Estados Unidos

Palabras clave

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

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Conducción de Automóvil / Accidentes de Tránsito Tipo de estudio: Prognostic_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Accid Anal Prev Año: 2021 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google