Research on Intelligent Reconstruction Method for Powered Two-wheeler Accident Based on Automatic Simulation and NSGA-Ⅱ Algorithm

doi:10.3901/JME.2023.24.197

Abstract

Abstract: Since manual accident reconstruction is strongly dependent on the experience and intuition of analysts with the trial-and-error method for parameter adjustment, the process is very time-consuming and the accuracy of results could not be guaranteed. An intelligent reconstruction approach is developed for powered two-wheelers(PTWs) combining automatic simulation and multi-objective optimization. Firstly, an automatic operation framework for multi-rigid models is established based on the ISIGHT program. Then, the non-dominated sorting genetic algorithm(NSGA-Ⅱ) with elite strategy is selected to optimize five position objectives, with 12 collisions parameters as design variables, and the head-vehicle collision area and lateral motion direction as constraints. Finally, two accident cases are reconstructed to verify effectiveness of the method. The results show that 480 simulations with the optimal solution are completed in 24 hours. The average error is below 5% with the maximum of 12.4%. Optimization process, convergence of the objective function, as well as the good consistency among the comparison between simulation and facts including the rest position, injury criteria, collision speed, kinematic response, demonstrate the effectiveness of the method. The intelligent method for PTWs accidents realizes automatic parameter adjustment, simulation operation, and result processing, which significantly improves the efficiency and ensures the accuracy of results. In general, the method coupling automatic operation and NSGA-Ⅱ algorithm can also be applied to other types of accident reconstruction.

Key words: powered two-wheeler, accident reconstruction, automatic simulation, multi-objective optimization, NSGA-Ⅱ

CLC Number:

TG156

LIU Yu, WAN Xinming, XU Wei, SHI Liangliang, BAI Zhonghao. Research on Intelligent Reconstruction Method for Powered Two-wheeler Accident Based on Automatic Simulation and NSGA-Ⅱ Algorithm[J]. Journal of Mechanical Engineering, 2023, 59(24): 197-208.

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