基于车辆变形深度的汽车安全有效性的评价与预测方法
Method to evaluate safety enhancement of the past and methodology to predict future enhancement based on vehicle deformation depth

事故数据库中的速度信息需要用基于能量守恒的事故再现方法来计算得到, 而不同车辆的刚度差异很难估计, 这导致所计算出的速度存在误差。这个问题直接影响到大部分用于估算驾驶员辅助系统有效性的方法的合理性, 因为这些方法需要使用事故所涉及的车辆的速度信息。该文提出了基于车辆变形深度的汽车安全有效性的评价与预测方法。通过分析德国事故数据, 证明了车辆变形深度相比于速度变化量能够更真实地反映事故严重程度。基于变形深度计算了过去30年汽车安全有效性的提高程度, 与历史数据吻合较好, 验证了基于变形深度的安全有效性评价方法的合理性。该文阐述了基于变形深度的驾驶员辅助系统安全有效性预测方法的思路。该预测方法仅需要事故数据库中准确的变形深度信息, 能够获得更多的事故数据支持, 从而可以更好地评价驾驶员辅助系统。
Abstract：Accident velocity information is difficult to obtain with accident reconstruction used to compute velocities, primarily using energy-based estimates. However, the different stiffnesses of the vehicles are difficult to estimate, which leads to significant uncertainty in the computed velocity. This is a major problem because most approaches for estimating the effect of driver assistant systems need the velocities of the involved vehicles. A method is given here to evaluate past safety enhancements to predict future enhancement based on the vehicle deformation depth. Analyses of German accident data show that for vehicles of significantly different stiffnesses, the vehicle deformation depth more truly reflects the severity of the accident than the velocity change. Vehicle safety enhancements over the past 30 years are then calculated based on the deformation depth. The results are in good agreement with historical data, which verifies the safety enhancement evaluation method using deformation depth information. A deformation-depth-based safety impact prediction method is also given for driver assistance systems. This prediction method uses the accurate deformation depth information in the accident database to improve evaluations of driver assistance systems.