多车事故链及碰撞概率建模与仿真
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- 英文论文题名：Multi Vehicle Accident Chain and Collision Probability Modeling and Simulation
- 论文作者：曹福贵 ; 江浩斌 ; 朱畏畏
- 英文论文作者：Cao Fugui ; Jiang Haobin ; Zhu Weiwei ; School of Automobile and Traffic Enginering ; Jiangsu University ; Road and Bridge Department ; Jiangsu Jiaotong College
- 年：2016
- 作者机构：江苏大学汽车与交通工程学院;江苏省交通技师学院路桥系;
- 论文关键词：连环交通事故 ; 多车事故链 ; 马尔科夫特性 ; 蒙特卡洛 ; 风险 ; 预警
- 英文论文关键词：serial traffic accident ; multi vehicle accident chain ; Markov property ; Monte Carlo ; risk ; warning
- 会议召开时间：2016-10-26
- 会议录名称：2016中国汽车工程学会年会论文集
- 英文会议录名称：Proceedings of 2016 SAE-China Congress
- 语种：中文
- 分类号：U467.14;U491.31
- 学会代码：QCGC
- 会议名称：2016中国汽车工程学会年会暨展览会
- 会议地点：中国上海
- 主办单位：中国汽车工程学会
- 学会名称：中国汽车工程学会
- 页数：5
- 文件大小：879k
- 原文格式：O
- 会议级别：全国
摘要
为了度量连环交通事故发生的风险,建立了以车辆为节点的多车事故链(MVAC),并对事故链碰撞概率进行建模分析。行驶的车辆因两车间碰撞概率的存在而成单链,区域内链接的单链形成事故链,分析表明多车事故链具有马尔科夫特性。通过对车辆的制动过程进行分析,建立了二维滚动制动和滑动制动下的绝对安全距离、相对安全距离模型,采用蒙特卡洛法对两车碰撞概率进行分析求解。根据多车事故链的马尔科夫特性,搭建多车事故链状态空间图及状态转移概率矩阵,建立了节点状态出现概率和多车事故链发生概率模型。为了验证模型的有效性,搭建了基于PreScan/SIMULINK联合仿真平台,进行单车道4车事故链发生概率仿真分析。仿真结果表明,所建立的模型能准确的表征多车事故风险,能实时对连环交通事故进行有效预警。
In order to measure the risk in serial traffic accident,a vehicle for multi vehicle accident chain node is established,and MVAC collision probability is modeled.Because of the presence of the two-car collision probability,the two-car linked into single chain,and all single chains in the region form the accident chain,and analysis shows that the MVAC with Markov property.Through analysis of the vehicle brake process,absolutely safe distance model and relatively safe distance model are established on two- dimensional scroll brake and sliding brake,and the two- car collision probability is solved with Monte Carlo method.According to MVAC Markov property,accident chain state space diagrams and state transition probability matrix are built,and the model of node state occurrence probability and MVAC occurrence probability is established.In order to verify the validity of the model,a united simulation platform based on PreScan/SIMULINK is built,and a simulation on four cars in a single lane MVAC occurrence probability is carried out.The simulation results show that the model can be used to characterize the risk of MVAC accurately,and it can be an effective early warning for serial traffic accident in real time.
In order to measure the risk in serial traffic accident,a vehicle for multi vehicle accident chain node is established,and MVAC collision probability is modeled.Because of the presence of the two-car collision probability,the two-car linked into single chain,and all single chains in the region form the accident chain,and analysis shows that the MVAC with Markov property.Through analysis of the vehicle brake process,absolutely safe distance model and relatively safe distance model are established on two- dimensional scroll brake and sliding brake,and the two- car collision probability is solved with Monte Carlo method.According to MVAC Markov property,accident chain state space diagrams and state transition probability matrix are built,and the model of node state occurrence probability and MVAC occurrence probability is established.In order to verify the validity of the model,a united simulation platform based on PreScan/SIMULINK is built,and a simulation on four cars in a single lane MVAC occurrence probability is carried out.The simulation results show that the model can be used to characterize the risk of MVAC accurately,and it can be an effective early warning for serial traffic accident in real time.
引文
[1]公安部交通管理局.2014中华人民共和国道路交通事故统计年报[R].无锡:公安部交通管理局,2015.
[2]吉德志,何波,赵璇,于青.基于蒙特卡洛方法的碰撞预警系统仿真[J].微计算机信息,2009,25(21):197-199.
[3]M.valdes-Vela,R.Toledo,F.Terroso-saenz,M.A.Zamora-Izquierdo.An application of a fuzzy classifier extracted form data for collision avoidance support in road vehicles[J].Engineering Application of Artificial Intelligence,2013,26:173-183.
[4]Jinn-Tsai Wong,Yi-Shih Chung,Rough set approach for accident chains exploration.Accident Analysis and Prevention,2007,39:629-637.
[5]马明,严新平,吴超仲.基于系统动力学的车辆追尾事故仿真分析模型[J].系统仿真学报,2009,21(11):3161-3165.
[6]陆斯文,张兰芳,方守恩.高速公路追尾机理概率分析及风险评价[J].同济大学学报,2011,39(8):1150-1154.
[7]Yunteng Lao,Guohui zhang,Yinhai Wang,John Milton.Generalized nonlinear models for rear-end crash risk analysis[J].Accident Analysis and Prevention,2014,62:9-16.
[8]Cong Chen,Guohui Zhang,Rafiqul Tarefder,Jianming Ma,Heng Wei,Hongzhi Guand.A multinomial logit model-Bayesian network hybrid approach for driver injury severity analyses in rear-end crashes[J]Accident Analysis and Prevention.2015,80:76-88.
[9]Chengcheng Xu,Wei Wang,Pan Liu,Rui Guo,Zhibin Li.Using the Bayesian updating approach to improve the spatial and temporal transferability of real-time crash risk prediction models[J]Transportation Research Part C,2014,38:167-176.
[10]Chengcheng Xu,Wei Wang,Pan Liu,Zhibin Li.Calibration of crash risk models on freeways with limited realtime traffic data using Bayesian meta-analysis and Bayesian inference approach[J]Accident Analysis and Prevention.2015,85:207-218.
[11]Rongjie Yu,Xuesong Wang,Kui Yang,Mohamed Abdel-Aty.Crash risk analysis for Shanghai urban expressways:A Bayesian semi-parametric modeling approach[J]Accident Analysis and Prevention.2015,86:211-219.
[12]Shahrzad Faghih-Roohi,Min xie,Kien Ming Ng.Accident risk assessment in marine transportation via Markov modeling and Markov chain Monte carlo simulation[J].Ocean Engineering,2014,91:363-370.
[13]HAKKANEN H,SUMMALA H.Fatal traffic accidents among trailer truck drivers and accident causes as viewed by other truck drivers[J].Accident Analysis and Prevention,2001,33(2):187-196.
[14]许伦辉,罗强,吴建伟,黄艳国.基于最小安全距离的车辆跟驰模型研究[J].公路交通科技,2010,27(10):95-106.
[15]王殿海,金盛.车辆跟驰行为建模的回顾与展望[J].中国公路学报,2012,25(1):115-124.
[2]吉德志,何波,赵璇,于青.基于蒙特卡洛方法的碰撞预警系统仿真[J].微计算机信息,2009,25(21):197-199.
[3]M.valdes-Vela,R.Toledo,F.Terroso-saenz,M.A.Zamora-Izquierdo.An application of a fuzzy classifier extracted form data for collision avoidance support in road vehicles[J].Engineering Application of Artificial Intelligence,2013,26:173-183.
[4]Jinn-Tsai Wong,Yi-Shih Chung,Rough set approach for accident chains exploration.Accident Analysis and Prevention,2007,39:629-637.
[5]马明,严新平,吴超仲.基于系统动力学的车辆追尾事故仿真分析模型[J].系统仿真学报,2009,21(11):3161-3165.
[6]陆斯文,张兰芳,方守恩.高速公路追尾机理概率分析及风险评价[J].同济大学学报,2011,39(8):1150-1154.
[7]Yunteng Lao,Guohui zhang,Yinhai Wang,John Milton.Generalized nonlinear models for rear-end crash risk analysis[J].Accident Analysis and Prevention,2014,62:9-16.
[8]Cong Chen,Guohui Zhang,Rafiqul Tarefder,Jianming Ma,Heng Wei,Hongzhi Guand.A multinomial logit model-Bayesian network hybrid approach for driver injury severity analyses in rear-end crashes[J]Accident Analysis and Prevention.2015,80:76-88.
[9]Chengcheng Xu,Wei Wang,Pan Liu,Rui Guo,Zhibin Li.Using the Bayesian updating approach to improve the spatial and temporal transferability of real-time crash risk prediction models[J]Transportation Research Part C,2014,38:167-176.
[10]Chengcheng Xu,Wei Wang,Pan Liu,Zhibin Li.Calibration of crash risk models on freeways with limited realtime traffic data using Bayesian meta-analysis and Bayesian inference approach[J]Accident Analysis and Prevention.2015,85:207-218.
[11]Rongjie Yu,Xuesong Wang,Kui Yang,Mohamed Abdel-Aty.Crash risk analysis for Shanghai urban expressways:A Bayesian semi-parametric modeling approach[J]Accident Analysis and Prevention.2015,86:211-219.
[12]Shahrzad Faghih-Roohi,Min xie,Kien Ming Ng.Accident risk assessment in marine transportation via Markov modeling and Markov chain Monte carlo simulation[J].Ocean Engineering,2014,91:363-370.
[13]HAKKANEN H,SUMMALA H.Fatal traffic accidents among trailer truck drivers and accident causes as viewed by other truck drivers[J].Accident Analysis and Prevention,2001,33(2):187-196.
[14]许伦辉,罗强,吴建伟,黄艳国.基于最小安全距离的车辆跟驰模型研究[J].公路交通科技,2010,27(10):95-106.
[15]王殿海,金盛.车辆跟驰行为建模的回顾与展望[J].中国公路学报,2012,25(1):115-124.