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A research on vehicle accident reconstruction using inverse problem analysis

基于逆问题分析的车辆事故重构研究

基本信息

批准号：
18560229
负责人：
MINAMOTO Hirofumi
金额：
$ 2.39万
依托单位：
Toyohashi University of Technology
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2006
资助国家：
日本
起止时间：
2006 至 2007
项目状态：
已结题

项目摘要

Accidents of vehicle collision are serious problem in our society today. Accident reconstruction contains the process that seeks the vehicle pm-impact speeds from the post-impact vehicle rest position. This is understood as one of the inverse problems which reconstruct the cause of the incident from the post-incident results. The purpose of this research is to construct the method of inverse analysis for the vehicle collision accidents, lb solve the vehicle collision accident inversely the artificial neural network technique was used in this research. The results of this research are as followings1. The vehicle collision accident was divided into two stages: vehicle collision and post-impact motion. The inverse analyses were carried out by using artificial neural network for each stage. By using the both inverse analyses sequentially, the pre-impact vehicle speeds were reconstructed from the final vehicle rest positions. In this research, the vehicle pre-impact speeds were reconstructe … More d in the reasonable accuracy for right angled side impact accident. This time, only the right angled collision accidents were examined. But the validity of this method has to be examined for other impact configurations in near fixture.2. In the learning process of the artificial neural network, supervised signals for the post-impact vehicle motion were made by detailed vehicle dynamics model using CarSim simulation software. On the other hand, the rigid body collision theory, which may give physically rational but practically rough estimations of pre- and poet- impact speeds, was used to make the supervised signal for the vehicle impact speeds. Therefore, the results of this time of research do not have enough accuracy for practical reconstruction. However, they may be used as a first estimation for the detailed reconstruction at the present.3. When more accurate and systematic supervised signals axe available, the accuracy of this method will increase naturally. Of course, the frame work which constructed in this research will be still valid for such caws and have a possibility to carry out more accurate inverse analyses Less

汽车碰撞事故是当今社会的一个严重问题。事故再现包含从碰撞后车辆静止位置寻求车辆pm碰撞速度的过程。这被理解为从事件后的结果重建事件原因的逆问题之一。本研究的目的是建立汽车碰撞事故的反分析方法，将人工神经网络技术应用于汽车碰撞事故的反分析中。本研究的结果如下1.将汽车碰撞事故分为汽车碰撞和碰撞后运动两个阶段。利用人工神经网络对各阶段进行了反演分析。通过顺序使用这两个逆分析，从最终的车辆静止位置重建碰撞前的车辆速度。在本研究中，汽车碰撞前的速度重建， ...更多信息 d在直角侧面碰撞事故中的合理准确度。这一次，只检查了直角碰撞事故。但是，该方法的有效性还有待于对其它近场碰撞构型的验证.在人工神经网络的学习过程中，利用CarSim仿真软件建立了详细的车辆动力学模型，生成了碰撞后车辆运动的监督信号。另一方面，刚体碰撞理论，它可以给出物理上合理的，但实际上是粗略的估计的预碰撞速度和后碰撞速度，被用来制作汽车碰撞速度的监督信号。因此，这一次的研究结果不具备足够的精度进行实际重建。然而，它们可以用作当前详细重建的第一估计。当有更精确、更系统的监测信号时，这种方法的精度自然会提高。当然，本研究所建立的框架对这类caws仍然有效，并有可能进行更精确的反分析。