基于遗传算法的高精度事故重建与损伤分析

doi:10.19562/j.chinasae.qcgc.2021.12.007

Abstract

Abstract:

In order to enhance the reconstruction accuracy of traffic accidents， the risk of pedestrian craniocerebral injury is analyzed，the multi-rigid-body model for accident vehicle is built based on 3D laser scanning technology， and the multi-objective genetic algorithm is used to obtain the optimal approximate solution. A coupled model is set up with optimization software ISIGHT and multi-rigid-body dynamics software MADYMO and the kinematic response of the human-vehicle collision is accurately reconstructed. Finally， finite element dummy model THUMS is adopted to predict the risk of craniocerebral injury. The results show that the reverse reconstruction of accident vehicle has a good result， the optimized human-vehicle kinematic behaviors are consistent with that in surveillance video， and the injury position and injury situation of dummy's head completely agree with the injury report.

Key words: accident reconstruction, 3D laser scanning technology, rigid multibody dynamics, genetic algorithm, finite element, craniocerebral injury

Chengming Wang,Ying Fan,Donghua Zou,Jinming Wang,Zhengdong Li,Yijiu Chen,Liangwei Zhong. High-accuracy Accident Reconstruction and Injury Analysis Based on Genetic Algorithm[J].Automotive Engineering, 2021, 43(12): 1787-1792.

Figures/Tables 10

References 19

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优化变量	最小值	最大值
D/m	0	0.6
v/（m·s^-1）	12.5	15.27
α/rad	0.52	1.05
β/rad	-0.2	0.2
γ/rad	-0.3	0.1

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High-accuracy Accident Reconstruction and Injury Analysis Based on Genetic Algorithm

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