货车与电动两轮车碰撞形态对骑车人运动学及损伤分析

doi:10.3969/j.issn.1674-8484.2025.06.005

摘要/Abstract

摘要： 探究了货车与电动两轮车碰撞事故中碰撞形态与骑车人运动学响应及损伤特征的关联性。筛选263例视频样本，提取车辆类型、碰撞角度和碰撞速度等参数；采用多体建模软件MADYMO搭建典型场景，开展16组仿真，以分析碰撞角度和位置对骑车人运动学响应及损伤的影响。结果表明：碰撞角度超过110°时，骑车人头部伤害允许指标（HIC）和头部角加速度突然增大；至碰撞角度120°时，头部角加速度达到最大值（73.9 krad/s²），HIC为11 931。碰撞位置处于货车中心区域时，骑车人HIC（1 231~1 461）和头部角加速度（22.6~26.9 krad/s²）处于较低区间，头部损伤风险较小；而处于货车两侧时，骑车人胸部3 ms加速度为25.8g~121.8g，胸部损伤风险较小。因而，碰撞角度与位置均对骑车人运动学响应影响显著。

关键词: 碰撞事故, 电动两轮车, 货车, 骑行人损伤, 统计分析, 运动学响应

Abstract:

The relationship between collision patterns in truck-versus-electric-two-wheeler crashes, the kinematic responses of riders, and injury characteristics were investigated. 16 simulation experiments were constructed by using the multi-body modeling software MADYMO based on 263 scenario-related cases to analyze the collision angles and the positions. The results show that the head injury metrics (the head injury criterions (HIC) and the head angular accelerations) sharply increase when the collision angles exceeds 110°, with the peaking at the collision angle of 120° (the HIC of 11 931, the head angular acceleration of 73.9 krad/s²). When the collision position is in the central area of the truck, the cyclist’s HIC (1 231~1 461) and the head angular acceleration (22.6~26.9 krad/s²) fall within lower ranges, that means lower risk of head injury. When the collision occurs on either side of the truck, the cyclist’s chest 3-ms acceleration is 25.8g~121.8g, that means a lower risk of chest injury. Therefore, both the collision angle and the collision position have a significant impact on the cyclist’s kinematic response.

Key words: collision accidents, two-wheeled vehicles, trucks, rider injuries, statistical analysis, kinematic response

中图分类号:

U461.91

郑雯祥, 王丙雨, 杨垚, 龚悠, 秦利燕. 货车与电动两轮车碰撞形态对骑车人运动学及损伤分析[J]. 汽车安全与节能学报, 2025, 16(6): 859-866.

ZHENG Wenxiang, WANG Bingyu, YANG Yao, GONG You, QIN Liyan. Analysis of collision patterns in truck-bicycle accidents on injuries and the kinematic of rider[J]. Journal of Automotive Safety and Energy, 2025, 16(6): 859-866.

图/表 13

参考文献 22

[1]	刘朝晖. 电动车产业浪潮奔涌苏南[J]. 新民周刊, 2024(12): 56-59.
	LIU Chaohui. The wave of the electric vehicle industry is rushing to southern Jiangsu[J]. Xinmin Weekly, 2024(12): 56-59. (in Chinese)
[2]	杨扬, 杨小佳. 基于系统动力学的城市货车限行问题研究[J]. 公路交通科技, 2017, 34(5): 150-158.
	YANG Yang, YANG Xiaojia. Study on travel restriction of urban freight vehicles based on system dynamics[J]. J Highw Transport Res Dev, 2017, 34(5): 150-158. (in Chinese)
[3]	张道文, 李敏, 庞劭荣, 等. 重型货车与二轮车事故致因及其拓扑层级分析[J]. 汽车安全与节能学报, 2023, 14(2): 157-164.
	ZHANG Daowen, LI Min, PANG Shaorong, et al. A study on the dynamic response of an electric bicycle cyclist and a car collision[J]. J Autom Safe Energ, 2023, 14(2): 157-164. (in Chinese)
[4]	马兴会, 马国清, 冯居辉, 等. 电动两轮车及自行车与汽车碰撞损伤对比分析[J]. 汽车技术, 2021(3): 51-56.
	MA Xinghui, MA Guoqing, FENG Juhui, et al. Comparative analysis of collision damage between electric two-wheelers and bicycles and automobiles[J]. Autom Tech, 2021(3): 51-56. (in Chinese)
[5]	薛海涛, 李海波, 赵小羽, 等. 汽车—电动自行车与汽车—自行车碰撞中骑车人动力学响应对比研究[J]. 公路与汽运, 2021(6): 37-42.
	XUE Haitao, LI Haibo, ZHAO Xiaoyu, et al. Comparative study of cyclist dynamic response in automobile-electric bicycle and car-bicycle collision[J]. Highw Autom Appl, 2021(6): 37-42. (in Chinese)
[6]	胡林, 方胜勇, 陈强. 基于正交实验的汽车-两轮车碰撞事故再现的参数影响研究[J]. 汽车工程, 2016, 38(5): 567-573.
	HU Lin, FANG Shengyong, CHEN Qiang. A Research on the parameter influences of the accident reconstruction for a car-motorcycle collision based on orthogonal experiments[J]. Autom Engi, 2016, 38(5): 567-573. (in Chinese)
[7]	刘娜, 周华, 张道文, 等. 碰撞形态对两轮车及骑车人运动响应的影响研究[J]. 广西大学学报: 自然科学版, 2017, 42(6): 2089-2096.
	LIU Na, ZHOU Hua, ZHANG Daowen, et al. A study on effect of collision form on motion response of two-wheelers vehicles and riders[J]. J Guangxi Univ: Nat Sci Ed, 2017, 42(6): 2089-2096. (in Chinese)
[8]	农立勇, 李雅禄. 基于物联网的大货车盲区监控与预警辅助驾驶系统设计[J]. 时代汽车, 2025(8): 115-117.
	NONG Liyong, LI Yalu. Design of blind spot monitoring and early warning assisted driving system for large trucks based on the internet of things[J]. Autom Time, 2025(8): 115-117. (in Chinese)
[9]	Pokorny P, Drescher J, Pitera K, et al. Accidents between freight vehicles and bicycles, with a focus on urban areas[J]. Transport Res Rec, 2017, 25: 999-1007
[10]	Hickman J, Hanowski R, Bocanegra J. A synthetic approach to compare the large truck crash causation study and naturalistic driving data[J]. Accid Anal Prev, 2018, 112: 11-14. doi: S0001-4575(17)30444-X pmid: 29306085
[11]	张翔, 王丙雨, 杨垚, 等. 货车-两轮车前碰撞事故中骑行者运动学响应及损伤分析[J]. 汽车工程学报, 2024, 14(2): 294-303.
	ZHANG Xiang, WANG Bingyu, YANG Yao, et al. Analysis of kinematic response and injuries to riders in frontal collisions between trucks and two-wheelers[J]. J Autom Engi, 2024, 14(2): 294-303.
[12]	中华人民共和国公安部. GB/T 33195-2016: 道路交通事故车辆速度鉴定[S/OL]. (2016-12-13) http://c.gb688.cn/bzgk/gb/showGb?type=online&hcno=4477946C3B913E4307355223CB323A0B.
	Ministry of Public Security of the People’s Republic of China. GB/T 33195-2016: Identification for the speed of vehicle involved in road traffic accident[S/OL]. (2016-12-13) http://c.gb688.cn/bzgk/gb/showGb?type=online&hcno=4477946C3B913E4307355223CB323A0B. (in Chinese)
[13]	中华人民共和国公安部. GA/T 1133-2014: 基于视频图像的车辆行驶速度技术鉴定[S/OL]. (2014-02-10) https://std.samr.gov.cn/hb/search/stdHBDetailed?id=8B1827F218A9BB19E05397BE0A0AB44A.
	Ministry of Public Security of the People’s Republic of China. GA/T 1133-2014: Vehicle speed identification based on video[S/OL]. (2014-02-10) https://std.samr.gov.cn/hb/search/stdHBDetailed?id=8B1827F218A9BB19E05397BE0A0AB44A. (in Chinese)
[14]	韩学源, 金先龙, 张晓云, 等. 基于视频图像与直接线性变换理论的车辆运动信息重构[J]. 汽车工程, 2012, 34(12): 1145-1149.
	HAN Xueyuan, JIN Xianlong, ZHANG Xiaoyun, et al. Vehicle movement information reconstruction based on video images and DLT theory[J]. Autom Engi, 2012, 34(12): 1145-1149. (in Chinese)
[15]	杨垚, 王丙雨, 张翔, 等. 基于视频的电动两轮车-行人碰撞事故特征和场景分析[J]. 汽车安全与节能学报, 2025, 16(3): 396-404.
	YANG Yao, WANG Bingyu, ZHANG Xiang et al. Scenarios of electric two-wheeler and pedestrian collision accidents based on video information[J]. J Autom Safe Energ, 2025, 16(3): 396-404. (in Chinese)
[16]	韩勇, 贺伟, 李泉, 等. 基于视频信息的汽车碰撞事故中骑行人运动学响应分析[J]. 汽车安全与节能学报, 2017, 8(4): 381-387.
	HAN Yong, HE Wei, LI Quan, et al. Analysis of two-wheelers kinematics before/during/after vehicle collisions based on video records[J]. J Autom Safe Energ, 2017, 8(4): 381-387. (in Chinese)
[17]	国家市场监督管理总局. GB/T 10000—2023: 中国成年人人体尺寸[S/OL]. (2023-08-06) https://openstd.samr.gov.cn/bzgk/gb/newGbInfo?hcno=B19DCCA575D9406856ABF87A511EE11F.
	Ministry of Public Security of the People’s Republic of China. GB/T 10000—2023: Human dimensions of Chinese adults[S/OL]. (2023-08-06) https://openstd.samr.gov.cn/bzgk/gb/newGbInfo?hcno=B19DCCA575D9406856ABF87A511EE11. (in Chinese)
[18]	聂进, 张翔, 张越, 等. 货车-两轮车碰撞事故典型场景提取及关联规则分析[J]. 汽车安全与节能学报, 2024, 15(4): 503-510.
	NIE Jin, ZHANG Xiang, ZHANG Yue, et al. Typical accident scene extraction and accident factor association rules analysis for truck-two-wheeler collisions[J]. J Autom Safe Energ, 2024, 15(4): 503-510. (in Chinese)
[19]	胡经国, 朱晓勇, 丁冉冉, 等. 碰撞假人头部性能指标HIC36及HIC15的区别研究[J]. 汽车零部件, 2022(6): 30-33.
	HU Jingguo, ZHU Xiaoyong, DING Ranran, et al. Study on the difference between head injury criteria HIC₃₆ and HIC₁₅ of crash dummy[J]. Autom Parts, 2022(6): 30-33. (in Chinese)
[20]	Margulies S, Thibault L. A Proposed tolerance criterion for diffuse axonal injury in man[J]. J Biomech, 1992, 25(8): 917-923. pmid: 1639835
[21]	Ramli F, Yamazaki K. Optimal design of HGV front structure for pedestrian safety[J]. J Adva Mech Des Syst Manuf, 2012, 6(4): 541-557.
[22]	HUANG Yuan, ZHOU Qing, Caroline K, et al. Are riders of electric two-wheelers safer than bicyclists in collisions with motor vehicles?[J]. Accid Anal Prev, 2019, 134: Paper No 105336.

场景	方法
机动车直线行驶且摄像机位置固定。	逐帧法计算速度。
机动车转向、摄像机位置固定且视频画面中有可知距离的固定参考点(如人行横道线、地面交通标识等)。	通过DLT计算速度。
碰撞场景有对应的经验公式且其他方法失效。	引文[12]中对应场景经验公式计算速度。

场景	方法
机动车直线行驶且摄像机位置固定。	逐帧法计算速度。
机动车转向、摄像机位置固定且视频画面中有可知距离的固定参考点(如人行横道线、地面交通标识等)。	通过DLT计算速度。
碰撞场景有对应的经验公式且其他方法失效。	引文[12]中对应场景经验公式计算速度。

货车
长×宽×高	8.52 m×2.55 m×3.46 m
保险杠离地高度	0.60 m
整备质量	12.50 t
碰撞时总重	12.57 t
重心高度	1.50 m
电动两轮车
长×宽×高	1.725 m×0.07 m×1.090 m
轴距	1.25 m
碰撞时总质量	150 kg
车把离地高度	0.91 m
座位离地高度	0.77 m
摩擦因数
货车与电动两轮车	0.30~0.50
货车与骑车人	0.30~0.50
电动两轮车与骑车人	0.40~0.50
骑车人与地面	0.50~0.70
电动两轮车与地面	0.55~0.70

货车
长×宽×高	8.52 m×2.55 m×3.46 m
保险杠离地高度	0.60 m
整备质量	12.50 t
碰撞时总重	12.57 t
重心高度	1.50 m
电动两轮车
长×宽×高	1.725 m×0.07 m×1.090 m
轴距	1.25 m
碰撞时总质量	150 kg
车把离地高度	0.91 m
座位离地高度	0.77 m
摩擦因数
货车与电动两轮车	0.30~0.50
货车与骑车人	0.30~0.50
电动两轮车与骑车人	0.40~0.50
骑车人与地面	0.50~0.70
电动两轮车与地面	0.55~0.70

碰撞位置	位置工况	描述
左侧	1	货车与电动两轮车车头
	2	货车与骑车人中心
	3	货车与两轮车中心
中间	4	货车中轴线与两轮车车头
	5	货车中轴线与两轮车中心
	6	货车中轴线与两轮车车尾
右侧	7	货车与骑车人中心
	8	货车与两轮车中心
	9	货车与两轮车车尾