Terranova Paolo, Guo Feng, Perez Miguel A
Virginia Tech Transportation Institute, Virginia Polytechnic Institute and State University, Blacksburg, Virginia.
Department of Mechanical Engineering, Virginia Polytechnic and State University, Blacksburg, Virginia.
Traffic Inj Prev. 2025 May 6:1-8. doi: 10.1080/15389588.2025.2494235.
The objectives of this study are to: (1) evaluate the fatality risk of powered two-wheeler (PTW) riders in collisions with various types of opponent vehicles; (2) estimate the likelihood of different impact orientations between PTWs and other vehicles involved, and (3) develop an initial crash-based speed-fatality prediction model specific to the United States that controls for vehicle orientation.
Data was extracted from the National Highway Traffic Safety Administration's Crash Reporting Sampling System and the Fatality Analysis Reporting System covering 2017-2021. This data was used to estimate the fatality risks associated with various types of opponent vehicles involved in PTW crashes. The vehicles involved in each crash were coupled based on the vehicles' impact locations, and the effects of different vehicle orientations on fatality were estimated using odds ratio analysis. Multivariate logistic regressions were used to model the relationship between impact speed and fatality risk for front-end collisions involving PTWs.
Crashes involving buses and heavy trucks posed a significantly higher risk to PTW riders, with the fatality risk being four times greater compared to collisions with passenger vehicles. This risk varied based on impact orientation; frontal collisions with the front or sides of the opposing vehicle were the most dangerous, with fatality odds approximately four times higher than rear-end impacts. The speed-fatality prediction model showed the fatality risk increased with higher PTW travel speed while accounting for the expected higher fatality risk in crashes involving older riders, heavy vehicles, or un-helmeted riders.
The significant influence of opponent vehicle type on fatality risk in crashes involving PTWs highlights the need for further investigation into vehicle-specific crash prevention and mitigation strategies, especially for light and heavy trucks. Similarly, the high variability in fatality odds across different crash configurations underscores the importance of integrating impact orientation surrogate variables into injury prediction models. The speed-fatality prediction model developed in this study provides a foundational framework for evaluating the effectiveness of advanced rider assistance systems and other safety interventions that reduce crash speed. Future research should explore the benefits of such measures through simulation and real-world testing.
本研究的目的是：（1）评估电动两轮车（PTW）骑手与各类对向车辆碰撞时的死亡风险；（2）估计PTW与其他涉事车辆之间不同碰撞方向的可能性；（3）开发一个针对美国的、基于碰撞的初始速度-死亡预测模型，该模型可控制车辆方向。
数据取自美国国家公路交通安全管理局的碰撞报告抽样系统和死亡分析报告系统，涵盖2017年至2021年。这些数据用于估计与PTW碰撞中各类对向车辆相关的死亡风险。根据车辆的碰撞位置对每次碰撞中的涉事车辆进行配对，并使用比值比分析估计不同车辆方向对死亡的影响。多变量逻辑回归用于对涉及PTW的前端碰撞中碰撞速度与死亡风险之间的关系进行建模。
涉及公交车和重型卡车的碰撞对PTW骑手构成的风险显著更高，与乘用车碰撞相比，死亡风险高出四倍。这种风险因碰撞方向而异；与对向车辆的前部或侧面发生正面碰撞最为危险，死亡几率比追尾碰撞高出约四倍。速度-死亡预测模型显示，PTW行驶速度越高，死亡风险越高，同时考虑到在涉及老年骑手、重型车辆或未戴头盔骑手的碰撞中预期更高的死亡风险。
对向车辆类型对涉及PTW的碰撞中死亡风险有重大影响，这凸显了进一步研究针对特定车辆的防撞和减灾策略的必要性，特别是针对轻型和重型卡车。同样，不同碰撞配置下死亡几率的高度变异性强调了将碰撞方向替代变量纳入伤害预测模型的重要性。本研究开发的速度-死亡预测模型为评估先进骑手辅助系统和其他降低碰撞速度的安全干预措施的有效性提供了一个基础框架。未来的研究应通过模拟和实际测试探索此类措施的益处。
