Vulnerable road users' crash hotspot identification on multi-lane arterial roads using estimated exposure and considering context classification.

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第一作者： Nada,Mahmoud

第一单位： Department of Civil, Environmental, and Construction Engineering, University of Central Florida (UCF), Orlando, FL 32816-2450, United States. Electronic address: nada.mahmoud@knights.ucf.edu.

作者： Nada,Mahmoud ^[1] ; Mohamed,Abdel-Aty ^[2] ; Qing,Cai ^[3] ; Ou,Zheng ^[4]

作者单位： Department of Civil, Environmental, and Construction Engineering, University of Central Florida (UCF), Orlando, FL 32816-2450, United States. Electronic address: nada.mahmoud@knights.ucf.edu. ^[1] Department of Civil, Environmental, and Construction Engineering, University of Central Florida (UCF), Orlando, FL 32816-2450, United States. Electronic address: M.Aty@ucf.edu. ^[2] Department of Civil, Environmental, and Construction Engineering, University of Central Florida (UCF), Orlando, FL 32816-2450, United States. Electronic address: qingcai@knights.ucf.edu. ^[3] Department of Civil, Environmental, and Construction Engineering, University of Central Florida (UCF), Orlando, FL 32816-2450, United States. Electronic address: ouzheng1993@Knights.ucf.edu. ^[4]

关键词 Bicycle exposure Machine learning Pedestrian exposure Safety performance function Statistical model Vulnerable road user

主题词事故, 交通(Accidents, Traffic);环境设计(Environment Design);人类(Humans);模型, 统计学(Models, Statistical);安全(Safety)

DOI 10.1016/j.aap.2021.106294

PMID 34252582

发布时间 2021-08-24

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