基于多种优化算法的交通事故精准化重建与颅脑损伤风险评估
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国家自然科学基金项目(82171872),上海市自然科学基金项目(21ZR1464600),司法部司法鉴定重点实验室项目,上海市法医学重点实验室项目 ( 21DZ2270800),上海市司法鉴定专业技术服务平台 ( 19DZ2292700), 中央级科研院所基本科研业务费项目(GY2020G-4,GY2021G-5),大学生创新创业训练计划项目(S202110660012)


Accurate Reconstruction of Traffic Accident Based on Multiple Optimization Algorithms and Evaluation of Craniocerebral Injury Risk
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    目的 探究不同优化算法对精准化重建交通事故的影响。 方法 应用非支配排序遗传算法( non-dominated sorting genetic algorithm-II, NSGA-II)、邻域培养遗传算法( neighborhood cultivation genetic algorithm, NCGA)以及多目标粒子群优化算法(multi-objective particle swarm optimization, MOPSO)对 1 例真实案件的多刚体动力学重建进行优化,研究不同优化算法对收敛速度与最优近似解的影响,并将优化所得的最优初始碰撞参数作为有限元模拟的边界条件,将仿真得到的颅脑损伤预测结果与实际损伤进行比较。 结果 NCGA 算法在优化过程中收敛速度更快,结果更优,最优近似解重建所得行人-车辆碰撞的运动学响应与监控视频相符,颅脑损伤预测情况与尸体检验基本一致。 结论 通过优化算法和多刚体、有限元方法结合可以完成交通事故精确化重建,减少人为因素的影响。

    Abstract:

    Objective To investigate the effect of different optimization algorithms on accurate reconstruction of traffic accidents. Methods Non-dominated sorting genetic algorithm-II ( NSGA-II), neighborhood cultivation genetic algorithm (NCGA) and multi-objective particle swarm optimization (MOPSO) were used to optimize the multi-rigid body dynamic reconstruction of a real case. The effects of different optimization algorithms on convergence speed and optimal approximate solution were studied. The optimal initial impact parameters were simulated as boundary conditions of finite element method, and the simulated results were compared with the actual injuries. Results NCGA had a faster convergence speed and a better result in optimization process. The kinematic response of pedestrian vehicle collision reconstructed by the optimal approximate solution was consistent with the surveillance video. The prediction of craniocerebral injury was basically consistent with the cadaver examination. Conclusions The combination of optimization algorithm, rigid multibody and finite element method can complete the accurate reconstruction of traffic accidents and reduce the influence of human factors.

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范 颖,王成铭,王金明,李正东,邹冬华,黄 江.基于多种优化算法的交通事故精准化重建与颅脑损伤风险评估[J].医用生物力学,2023,38(2):346-352

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  • 收稿日期:2022-02-16
  • 最后修改日期:2022-04-12
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  • 在线发布日期: 2023-04-25
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