A Method of Predicting Minimal Vehicle Velocity in Vehicle-Pedestrian Accidents

doi:10.3969/j.issn.1000-565X.2014.12.006

Journal of South China University of Technology (Natural Science Edition) ›› 2014, Vol. 42 ›› Issue (12): 35-39.doi: 10.3969/j.issn.1000-565X.2014.12.006

• Traffic & Transportation Engineering • Previous Articles Next Articles

A Method of Predicting Minimal Vehicle Velocity in Vehicle-Pedestrian Accidents

Zhang Yong-gang¹ Xu Jian-Min¹ Zou Tie-fang² Liu Yu²

1.School of Civil Engineering and Transportation,South China University of Technology,Guangzhou 510640,Guangdong,China;2.School of Automotive and Mechanical Engineering,Changsha University of Science and Technology,Changsha 410004,Hunan,China

Received:2014-06-17 Revised:2014-08-13 Online:2014-12-25 Published:2014-11-17
Contact: 邹铁方(1982-)，男，副教授，主要从事道路交通事故再现研究． E-mail:tiefang@163.com
About author:张勇刚(1977-)，男，博士生，副教授，主要从事道路交通事故再现研究．E-mail:zysteel@163．com
Supported by:
国家自然科学基金资助项目 (51208065);同济大学道路与交通工程教育部重点实验室开放基金资助项目(201203);湖南省高等学校科学研究项目(12C0017)

Abstract

Abstract:

In order to provide a reliable approximate vehicle velocityd for simulating a vehicle-pedestrian accident,the relationship between the flight-phase distance of pedestrian and the vehicle velocity is derived,based on theclassical mechanics and some hypotheses.Then,two useful prediction models of minimal vehicle velocity are ob-tained,and one of them is used for a flat road while the other is used for a slope.Moreover,the two models are ver-ified by comparing the existing researches with the simulation results obtained through Pc-Crash.It is found that thetwo models are effective and feasible.Finally,the two models are further verified by a real vehicle-pedestrian acci-dent.

Key words: traffic accidents, vehicle-pedestrian accident, flight-phase distance, velocity analyzers, slope

CLC Number:

U491.3

Zhang Yong-gang Xu Jian-Min Zou Tie-fang Liu Yu . A Method of Predicting Minimal Vehicle Velocity in Vehicle-Pedestrian Accidents[J]. Journal of South China University of Technology (Natural Science Edition), 2014, 42(12): 35-39.

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A Method of Predicting Minimal Vehicle Velocity in Vehicle-Pedestrian Accidents

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