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作 者:于琪 马路[1,2] YU Qi;MA Lu(School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China;Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport,Beijing 100044,China)
机构地区:[1]北京交通大学交通运输学院,北京100044 [2]综合交通运输大数据应用技术交通运输行业重点实验室,北京100044
出 处:《综合运输》2024年第9期114-119,共6页China Transportation Review
基 金:国家重点研发计划资助项目(2023YFC3009600)。
摘 要:本文旨在研究不同动力类型车辆碰撞事故中乘员伤害严重程度特征及其主要影响因素。交通事故数据选自美国国家公路交通安全管理局GES系统中2020和2021年的数据集,并引入固有匹配对的数据结构解决电动汽车和燃油汽车事故数据量差异过大的问题。利用贝叶斯模型深入挖掘人员层面、环境层面等变量对道路交通事故乘员伤害严重程度的影响机理,并据此给出了解释和针对性的事故预防措施。主要结论包括:与干燥路面相比,路面潮湿时,电动汽车无伤害的几率增加,而燃油汽车事故导致致残/致命碰撞的几率增加。与多条车道相比,燃油汽车在两车道上的事故伤害程度低,而电动汽车在两车道上发生碰撞事故后更容易导致致残/致命伤害。This article aims to study the severity characteristics and main influencing factors of passenger injuries in collision accidents of vehicles with different power types.The traffic accident data was selected from the 2020 and 2021 datasets in the National Highway Traffic Safety Administration's GES system,and an inherent matching data structure was introduced to address the issue of significant differences in the amount of accident data between electric and fuel powered vehicles. Utilizing Bayesian models to delve into the impact mechanismof variables such as personnel and environment on the severity of passenger injuries in road traffic accidents,and based on this, provide explanations and targeted accident prevention measures. The main conclusionsinclude: compared to dry road surfaces, when the road surface is wet, the probability of electric vehicles beingharmless increases, while the probability of fuel vehicle accidents leading to disability/fatal collisions increases.Compared to multiple lanes, gasoline powered vehicles have a lower degree of injury in accidents on twolanes, while electric vehicles are more likely to cause disability/fatal injury in collisions on two lanes.
关 键 词:交通安全 伤害严重程度 固有匹配对 贝叶斯模型 电动汽车
分 类 号:U491[交通运输工程—交通运输规划与管理]
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