The Global Status Report on Road Safety released by the World Health Organization indicates that approximately 1.35 million people die in road traffic crashes each year ( WHO, 2018). This study indicated that multibody simulations coupled with optimization algorithms can be used to accurately reconstruct vehicle-pedestrian collisions. NSGA-II converged within 100 generations. In addition, when all vehicle-pedestrian-ground contacts were considered, the results showed a better match in terms of kinematic response. Based on the results of the reconstruction of a real-world accident, the present study indicated that NSGA-II had better convergence and generated more noninferior solutions and better final solutions than NCGA and MOPSO.
The final reconstructed results were compared with the process of a real accident. The effect of the number of objective functions, the choice of different objective functions and the optimal number of iterations were also considered. Three common multiobjective optimization algorithms-nondominated sorting genetic algorithm-II (NSGA-II), neighbourhood cultivation genetic algorithm (NCGA), and multiobjective particle swarm optimization (MOPSO)-were compared. The objective function of the optimization problem was defined as the Euclidean distance between the known vehicle, human and ground contact points, and multiobjective optimization algorithms were employed to obtain the local minima of the objective function. The purpose of this study is to explore the use of an improved optimization algorithm combined with MADYMO multibody simulations and crash data to conduct accurate reconstructions of vehicle–pedestrian accidents. The incident data for a crash, such as vehicle deformation, injury of the victim, distance of initial position and rest position of accident participants, are useful for verification in MAthematical DYnamic MOdels (MADYMO) simulations. In vehicle–pedestrian accidents, the preimpact conditions of pedestrians and vehicles are frequently uncertain. 2Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, China.1School of Forensic Medicine, Guizhou Medical University, Guiyang, China.Donghua Zou 1,2 †, Ying Fan 1,2 †, Ningguo Liu 2, Jianhua Zhang 2, Dikun Liu 1, Qingfeng Liu 1, Zhengdong Li 2*, Jinming Wang 2* and Jiang Huang 1*
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