Real-time crash identification using connected electric vehicle operation data.

Zhu, Meixin; Yang, Hao Frank; Liu, Chenxi; Pu, Ziyuan; Wang, Yinhai

Zhu, Meixin; Yang, Hao Frank; Liu, Chenxi; Pu, Ziyuan; Wang, Yinhai.

Afiliação

Zhu M; Department of Civil and Environmental Engineering, University of Washington, United States. Electronic address: meixin92@uw.edu.
Yang HF; Department of Civil and Environmental Engineering, University of Washington, United States. Electronic address: haoya@uw.edu.
Liu C; Department of Civil and Environmental Engineering, University of Washington, United States. Electronic address: lcx2017@uw.edu.
Pu Z; School of Engineering, Monash University, Australia. Electronic address: ziyuan.pu@monash.edu.
Wang Y; Department of Civil and Environmental Engineering, University of Washington, United States. Electronic address: yinhai@uw.edu.

Accid Anal Prev ; 173: 106708, 2022 Aug.

Article em En | MEDLINE | ID: mdl-35640365

Assuntos

Acidentes de Trânsito; Condução de Veículo; Acidentes de Trânsito/prevenção & controle; Algoritmos; Automóveis; Humanos; Tecnologia

Palavras-chave

Anomaly detection; Connected vehicle; Crash recognition; Electric vehicles; Intelligent transportation

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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 2_ODS3 Base de dados: MEDLINE Assunto principal: Condução de Veículo / Acidentes de Trânsito Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Accid Anal Prev Ano de publicação: 2022 Tipo de documento: Article

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