基于乘员伤害分析的路侧行道树事故严重度评价

为了定量评估公路路侧行道树事故严重度，有针对性地提出安全改善措施，以减少车辆与路侧行道树碰撞的事故损失，分别引入加速度严重性指数（Acceleration Severity Index，ASI）、头部损伤判据（Head Injury Criteria，HIC）和胸部合成加速度（Chest Resultant Acceleration，CRA）作为乘员伤害指标；利用PC-crash汽车动力学仿真软件构建车辆刚体系统和乘员多体系统，通过设置不同车辆驶出速度、平曲线半径、行道树直径和行道树间距，分别开展小型车、大型车与路侧行道树的偏置碰撞试验，共收集2 256组数据；针对公路直线段和曲线段，分别拟合了基于CRA的小型车乘员伤害评估模型，以及基于ASI的大型车和小型车乘员伤害评估模型；根据Fisher最优分割法确定了路侧行道树事故严重度的合理评价等级及各级对应的ASI和CRA阈值，给出了基于CRA和ASI的路侧行道树事故严重度评价方法；随后提出了一种新的用于评估事故严重度分级准确性的指标-误分级程度，并将其应用于事故严重度评价方法的有效性验证中；最后将大型车比例引入ASI评估模型中并改进了模型。研究结果表明：在相同仿真试验条件下，驾驶人胸部损伤比头部损伤更严重，小型车ASI平均值大于大型车ASI平均值；CRA，ASI与驶出速度近似呈正线性相关，与行道树直径近似呈对数相关；行道树间距越大、平曲线半径越小，则车辆遭受二次碰撞的几率越小，乘员伤害风险越低；在案例分析中，2种分别基于CRA和ASI的路侧行道树事故严重度评价方法评价结果基本一致，且误分级程度分别为4.7%和4.3%，验证了提出的路侧行道树事故严重度评价方法的准确性，并证实了ASI可作为评估路侧行道树事故中乘员伤害的有效指标。

Severity Assessment of Roadside Tree Accidents Based on Occupant Injury Analysis

The aim of this study was to quantitatively assess the severity of roadside tree accidents,and propose specific safety measures to reduce the losses in roadside tree accidents.This study used the head injury criteria(HIC),acceleration severity index(ASI),and chest resultant acceleration(CRA)as the indexes of occupant injuries.An occupant many-body system and vehicle rigid body system were constructed,and bias collision tests between cars,trucks,and trees were carried out by setting different variables(i.e.,vehicle departure speed,horizontal radius,tree diameter,and tree distance)in PC-crash software.Eventually,2256 sets of data were obtained.For the straight and curved sections of the highways,the occupant injury assessment models of cars based on the CRA and the occupant injury assessment models of trucks and cars based on the ASI were fitted,respectively.By using the Fisher optimal segmentation method,reasonable classification criteria of the roadside tree accident severity and the corresponding thresholds of ASI and CRA were given,and severity evaluation methods of roadside tree accidents based on the CRA and the ASI,respectively,were proposed.Moreover,a new indicator to assess the validity of the accident severity classification,which is the degree of misclassification,was built and used to validate the proposed evaluation methods.Finally,the proportion of trucks was introduced into the ASI assessment model to further improve the proposed model.The results show that under the same conditions as the simulation test,driver chest injuries are more serious than head injuries,and the average ASI for cars is greater than for trucks.Further,the CRA and the ASI have a logarithmic correlation with the tree diameter and a positive linear correlation with the vehicle departure speed;the smaller the horizontal radius and the larger the distance between the trees,the smaller the chance of vehicles suffering a second collision,and the lower the risk of occupant injury.In the case analysis,the assessment results from these two proposed evaluation methods based on the CRA and the ASI are basically consistent,and the degrees of misclassification are 4.7%and 4.3%,respectively.This not only confirms the validity of the proposed evaluation methods,but also verifies that the ASI can be used as an effective indicator to evaluate occupant injuries in roadside tree accidents.