V2X环境下基于圆风险域的交通冲突识别模型  

Traffic conflict recognition model based on circular risk region under V2X environment

作　　者：赵红专 代静 张继康 李文勇[1] 展新 周旦[1] ZHAO Hongzhuan;DAI Jing;ZHANG Jikang;LI Wenyong;ZHAN Xin;ZHOU Dan(Guangxi Key Laboratory of Intelligent Transportation System(ITS),Guilin University of Electronic Technology,Guilin 541004,Guangxi Province,P.R.China;Dongfeng Liuzhou Automobile Co.Ltd.,Liuzhou 545000,Guangxi Province,P.R.China)

机构地区：[1]桂林电子科技大学广西智慧交通重点实验室,广西桂林541004 [2]东风柳州汽车有限公司商用车技术中心,广西柳州545000

出　　处：《深圳大学学报（理工版）》2024年第1期74-82,共9页Journal of Shenzhen University(Science and Engineering)

基　　金：国家自然科学基金资助项目(52362045);广西科技重大专项资助项目(桂科AA22068101);广西重点研发计划项目(桂科AB21220052);柳州市科技重大专项资助项目(2021CAA0101);桂林电子科技大学研究生教育创新计划资助项目(2022YCXS228);桂林市创新平台和人才计划资助项目(20210217-15);广西精密导航技术与应用重点实验室开放课题资助项目(DH202225)

摘　　要：为提高快速路匝道区域合流冲突的识别精度,并缓解合流冲突提供决策依据,提出一种V2X(vehicle to everything)环境下基于圆风险域的交通冲突识别模型.通过V2X技术实时获取车辆位置和速度,以冲突风险时间为关键参数,分析主线车辆和匝道车辆的不同运动状态特性;引入风险域概念,结合车辆运动学,构建基于圆风险域冲突识别模型,进而通过两圆的位置关系表征两车之间的运动关系,实现交通冲突的识别;为细化冲突风险程度,采用累计频率曲线法判定冲突风险程度等级.仿真结果表明,采用冲突识别模型的识别率相比未采用时提高25.81%,说明该模型能有效识别匝道合流冲突,提高通行效率,并可为V2X环境下匝道合流车辆提供安全预警.To improve the identification accuracy of merging conflicts in expressway ramp area and provide decisionmaking basis for mitigating merging conflicts,we propose a traffic conflict recognition model based on circular risk region under vehicle to everything(V2X)environment.Through real-time acquisition of vehicle positions and speeds using V2X technology,with conflict risk time as a key parameter,the different motion characteristics of mainline and ramp vehicles are analyzed.Firstly,by combining the vehicle kinematics,we introduce the risk region concept to construct a conflict recognition model based on circular risk region.Then,by analyzing the positional relationship of two circles given by the main line vehicle and the ramp vehicle,we characterize the relationship between two vehicles and achieve the recognition of traffic conflicts.Finally,to refine the degree of conflict risk,we use the cumulative frequency curve method to determine the level of conflict risk.Simulation results show that the recognition rate of the conflict recognition model is 25.81%higher than that of the non-adoption model,which indicates that the model can effectively recognize ramp merging conflicts,improving the traffic efficiency,and provide safety warnings for ramp merging vehicles in V2X environment.

关 键 词：智能交通 车联网 入口匝道 冲突识别 风险域 累计频率曲线法 

分 类 号：U495[交通运输工程—交通运输规划与管理]