摘要In order to improve the safety of truck traffic on continuous downhill sections of highways, optimise traffic safety management or the design of traffic safety facilities, study in depth the risk of rear-end accidents of trucks on continuous downhill sections of highways, based on actual measurement data, put forward the evaluation index of rear-end risk considering the speed difference and headway time distance-Collision Deceleration Rate（CDR). Collision Reduction Rate (CDR). Firstly, the principle of risk of rear-end accidents of trucks on long downhill road sections is analysed, and the data of trucks travelling on long downhill road sections in a special control area of a western motorway are used to determine the risk influencing factors as speed difference and headway time distance; then, the distribution law of effective CDR data is analysed and calculated through fitting distribution test, and the 85% quantile value of its distribution is taken as the threshold value of dangerous CDR; finally, the collision potential index (CPI) is combined with the concept (CPI) to establish a CDR-based continuous downhill truck rear-end risk probability model. Based on the tailgating accident data in the special control area of the motorway, the CDR-based continuous downhill truck tailgating risk probability model is applied and tested, and the results show that: in the fitted distribution test, the CDR samples of the studied continuous downhill section obey lognormal distribution, and the threshold value of hazardous CDR is 0.4916 m/s2; there are more significant differences in the tailgating probability risk at different measurement points, while the tailgating risk at different The correlation coefficient between the accident rate data and the probability risk data is r(X,Y)=94.5%, which is a strong correlation, i.e. the trend of the accident rate data and the probability risk data is consistent, indicating that the CDR-based probability model of tailgating accident risk can provide a scientific assessment basis for the risk study of continuous downhill sections of highways, and the research method can be used for The study method can also be used as a reference for other sections of highways.
Abstract：In order to improve the safety of truck traffic on continuous downhill sections of highways, optimise traffic safety management or the design of traffic safety facilities, study in depth the risk of rear-end accidents of trucks on continuous downhill sections of highways, based on actual measurement data, put forward the evaluation index of rear-end risk considering the speed difference and headway time distance-Collision Deceleration Rate（CDR). Collision Reduction Rate (CDR). Firstly, the principle of risk of rear-end accidents of trucks on long downhill road sections is analysed, and the data of trucks travelling on long downhill road sections in a special control area of a western motorway are used to determine the risk influencing factors as speed difference and headway time distance; then, the distribution law of effective CDR data is analysed and calculated through fitting distribution test, and the 85% quantile value of its distribution is taken as the threshold value of dangerous CDR; finally, the collision potential index (CPI) is combined with the concept (CPI) to establish a CDR-based continuous downhill truck rear-end risk probability model. Based on the tailgating accident data in the special control area of the motorway, the CDR-based continuous downhill truck tailgating risk probability model is applied and tested, and the results show that: in the fitted distribution test, the CDR samples of the studied continuous downhill section obey lognormal distribution, and the threshold value of hazardous CDR is 0.4916 m/s2; there are more significant differences in the tailgating probability risk at different measurement points, while the tailgating risk at different The correlation coefficient between the accident rate data and the probability risk data is r(X,Y)=94.5%, which is a strong correlation, i.e. the trend of the accident rate data and the probability risk data is consistent, indicating that the CDR-based probability model of tailgating accident risk can provide a scientific assessment basis for the risk study of continuous downhill sections of highways, and the research method can be used for The study method can also be used as a reference for other sections of highways.
基金资助:Supported by the Science and Technology Project of Sichuan Provincial Department of Transportation (No.2021-ZL-15); the Sichuan Provincial Science and Technology Program Grant (No.2022YFG0048)
通讯作者:
ZOU Hai-yun
引用本文:
邹海云, 刘锴, 张驰, 马如鹏, 王博. Study on the Risk of Truck Rear-end Collision in Continuous Downhill Section of Expressway[J]. Journal of Highway and Transportation Research and Development, 2022, 16(4): 92-101.
ZOU Hai-yun, LIU Kai, ZHANG Chi, MA Ru-peng, WANG Bo. Study on the Risk of Truck Rear-end Collision in Continuous Downhill Section of Expressway. Journal of Highway and Transportation Research and Development, 2022, 16(4): 92-101.
[1] National Bureau of Statistics. China Statistical Yearbook 2019[M]. Beijing:China Statistics Press, 2019. (in Chinese) [2] Traffic Management Bureau of Ministry of Public Security. Road Traffic Accidents Statistical Annual Report of the People's Republic of China in 2014[R]. Beijing:Traffic Management Bureau of Ministry of Public Security, 2015. (in Chinese) [3] DING Nai-kan, ZHU Shun-ying, WANG Hong, et al. Structural Equation Model for Effects of Edge Line Markings on Risk of Rear-end Collision[J]. China Safety Science Journal, 2017, 27(3):106-110. (in Chinese) [4] LIU Xin-xin. Analysis of Influencing Factors and Prevention Countermeasures for Serious Degree of Expressway Rear-end Crash[D]. Changchun:Jilin University, 2016. (in Chinese) [5] ZHAO Yang-dong. Analysis of Causes and Prevention Countermeasures of Expressway Rear-end Crash Accident[D]. Harbin:Harbin Institute of Technology, 2007. (in Chinese) [6] ZHANG J J, WANG Y P, LU G Q. Impact of Heterogeneity of Car-following Behavior on Rear-end Crash Risk[J]. Accident Analysis and Prevention, 2019, 125:275-289. [7] LU Si-wen, ZHANG Lan-fang, FANG Shou-en. Probabilistic Analysis and Risk Evaluation of Highway Rear-end Collision[J]. Journal of Tongji University (Natural Science Edition), 2011, 39(8):1150-1154. (in Chinese) [8] SHI Hai-yan. Mechanism Analysis and Simulation Research of Expressway Vehicle Rear End Crash[D]. Changsha:Changsha University of Science and Technology, 2010. (in Chinese) [9] LIU Xiao-yang. Study on Probability Model and Simulation of Expressway Vehicle Rear-end Collision[D].Changsha:Changsha University of Science and Technology, 2009. (in Chinese) [10] YUAN Shou-li, GUO Zheng. A Warning Model for Vehicle Collision on Account of the Reaction Time of the Driver[J]. Journal of Safety and Environment, 2021, 21(1):270-276. (in Chinese) [11] MINDERHOUD M M, BOVY P H L. Extended Time-tocollision Measures for Road Traffic Safety Assessment[J]. Accident Analysis and Prevention, 2001, 33(1):89-97. [12] WANG Jia-li. Study on Mechanism of Risk of Expressway Serial Rear Crash on Fog Day[D]. Beijing:Beijing Jiaotong University, 2018. (in Chinese) [13] XU Hua-zhong, XIONG He-jin. Study on End Collision of Motorcars and Chaos Model of Traffic Flow[J]. Journal of Wuhan University of Technology (Transportation Science & Engineering Edition), 2006, 30(1):85-87. (in Chinese) [14] MENG Fan-xing, ZHANG Liang, ZHANG Wei. A Study on Drivers' Time Headway[J]. Industrial Engineering & Management, 2013, 18(2):131-135, 140. (in Chinese) [15] XU Jin, SUN Zi-qiu, LONG Yan-song, et al. Carfollowing Behavior of Passenger Cars on River Crossing Bridge Based on Naturalistic Driving Data[J]. China Journal of Highway and Transport, 2022, 35(5):170-1778. (in Chinese) [16] HUANG Chong-fu. Discussion on Basic Methods for Risk Analysis[J]. Journal of Natural Disasters, 2011, 20(5):1-10. (in Chinese) [17] PENG Yi-hua. High Definition Video Surveillance Information Acquisition System for Bayonet[J]. Automation & Instrumentation, 2017(11):84-86. (in Chinese) [18] ZHAO P B, LEE C. Assessing Rear-end Collision Risk of Cars and Heavy Vehicles on Freeways Using a Surrogate Safety Measure[J]. Accident Analysis and Prevention, 2018, 113:149-158.
2022, Vol. 16 
