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Injury Analysis of Vehicle-Pedestrian Collision Based on Orthogonal Experiments

Yuan Min1,†, Xu Fengxiang2,3,*, Wu Junhao1, Zheng Xuefeng1

1 Department of Automation Engineering, The Engineering & Technical College of Chengdu University of Technology, Leshan 614004, China
2 Hubei Key Laboratory of Advanced Technology of Automotive Components, Wuhan University of Technology, Wuhan 430070, China
3 Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan University of Technology, Wuhan 430070, China

* Corresponding Authors:Email of corresponding author: email
† Email: email

Computer Systems Science and Engineering 2020, 35(3), 173-181. https://doi.org/10.32604/csse.2020.35.173

Abstract

This paper studies the influence of different factors on pedestrian head injury in vehicle-pedestrian collisions. PC-Crash software is used to construct simulation experiments under ten factors. The research shows that the injury to pedestrians in reverse impact is greater than that to pedestrians in forward impact. With the acceleration of vehicle speed, the HIC value of pedestrians will increase with the increase of the height of the front hood from the ground. When the vehicle speed is less than 40 km/h, the injury to pedestrians in a forward-leaning emergency posture is smaller, and the injury to a standing emergency posture is the highest.

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APA Style
Min, Y., Fengxiang, X., Junhao, W., Xuefeng, Z. (2020). Injury analysis of vehicle-pedestrian collision based on orthogonal experiments. Computer Systems Science and Engineering, 35(3), 173-181. https://doi.org/10.32604/csse.2020.35.173
Vancouver Style
Min Y, Fengxiang X, Junhao W, Xuefeng Z. Injury analysis of vehicle-pedestrian collision based on orthogonal experiments. Comput Syst Sci Eng. 2020;35(3):173-181 https://doi.org/10.32604/csse.2020.35.173
IEEE Style
Y. Min, X. Fengxiang, W. Junhao, and Z. Xuefeng "Injury Analysis of Vehicle-Pedestrian Collision Based on Orthogonal Experiments," Comput. Syst. Sci. Eng., vol. 35, no. 3, pp. 173-181. 2020. https://doi.org/10.32604/csse.2020.35.173

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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