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Analysis of running child pedestrians impacted by a vehicle using rigid-body models and optimization techniques

机译:使用刚体模型和优化技术分析车辆行驶中的儿童行人

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摘要

Lack of information from vehicle-to-child pedestrian impacts provides considerable challenges when developing vehicle countermeasures for the pediatric population. Crash reconstructions of real-world incidents provide useful information about the vehicle damage and injury outcome but do not permit definitive and quantitative measures of the impact severity given the high level of uncertainty in the initial conditions of the pedestrian and the vehicle prior the impact. This paper develops an advanced methodology for reconstructing child pedestrian-vehicle impacts that combines the crash data with multi-body simulations and optimization techniques for identifying the pedestrian posture and vehicle speed prior to impact. For the child pedestrian posture, a continuous sequence of the running gait was developed based on the literature data and simulations. Using vehicle damage information from an actual child pedestrian crash, an objective function was developed that minimized the difference between vehicle and pedestrian contact points for the simulated child postures, pedestrian, and vehicle speeds. Simulated annealing and genetic optimization algorithms were used to identify sets of potential solutions for the pedestrian and vehicle initial conditions. Local minimums were observed for several response surfaces of the objective function which shows the non-convex nature of the crash reconstruction optimization problem with the chosen objective function. Based on the results of the real-world reconstruction, this study indicates that numerical simulations coupled with heuristic optimization algorithms can be used to reconstruct child pedestrian and vehicle pre-impact conditions.
机译:在制定针对儿科人群的车辆对策时,车辆对儿童的行人碰撞所产生的信息不足给我们带来了巨大的挑战。真实事件的碰撞重建提供了有关车辆损坏和伤害结果的有用信息,但鉴于行人和车辆在碰撞之前的初始条件存在很高的不确定性,因此无法对碰撞严重性进行确定和定量的评估。本文开发了一种先进的方法来重建儿童行人车辆碰撞,该方法将碰撞数据与多体仿真和优化技术相结合,以在碰撞前识别行人的姿势和车速。对于儿童行人姿势,根据文献数据和模拟结果,开发了连续的步态序列。利用来自实际儿童行人碰撞的车辆损坏信息,开发了一种目标函数,该函数将模拟儿童姿势,行人和车速的车辆和行人接触点之间的差异最小化。模拟退火和遗传优化算法用于识别行人和车辆初始条件的潜在解决方案集。观察到目标函数的几个响应面的局部最小值,这表明具有所选目标函数的碰撞重建优化问题的非凸性。基于真实世界重建的结果,这项研究表明,数值模拟与启发式优化算法可以用于重建儿童行人和车辆的预碰撞条件。

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