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作 者:赵睿 李云 胡宏宇[2] 高镇海[2] ZHAO Rui;LI Yun;HU Hong-yu;GAO Zhen-hai(College of Automotive Engineering,Jilin University,Changchun 130022,China;State Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun 130022,China)
机构地区:[1]吉林大学汽车工程学院,长春130022 [2]吉林大学汽车仿真与控制国家重点实验室,长春130022
出 处:《吉林大学学报(工学版)》2023年第4期1019-1029,共11页Journal of Jilin University:Engineering and Technology Edition
基 金:国家自然科学基金项目(52202494,52202495);吉林省自然科学基金项目(20210101064JC)。
摘 要:面向交通事故高发比例的无信号交叉口场景,提出了一种基于V2I通信的车辆碰撞预警方法,以保障行车安全。首先,提出路段与冲突区域匹配方法,筛选存在碰撞风险的车辆与冲突区域;在此基础上,提出两级冗余碰撞预警方法,包括用于车辆进入交叉口前的一级动态碰撞距离检测(DDTC)算法以及车辆进入交叉口后的二级圆形区域碰撞检测(CATC)算法。该方法通过网联信息弥补自车感知局限性,通过冲突区域匹配与安全距离过滤提高检测效率,通过动态距离差阈值设置提高检测准确率。基于NHTSA交叉口场景集的测试结果表明,该方法与具代表性的时间差法与距离差法相比,漏报率分别降低了约16%和6%,误报率分别降低了约88%和48%,检测时间均降低了约74%,具备更高的准确性和高效性。Facing the unsignalized intersection scenario with a high incidence of traffic accidents,a vehicle collision warning method based on V2I communication is proposed to ensure driving safety.First,a method for matching road segments and conflict areas is proposed to screen vehicles that are at risk of collision and the corresponding conflict areas.On this basis,a two-level redundant intersection collision warning method is proposed,including the Dynamic Distance to Collision(DDTC)algorithm,which is used to perform first-level collision warning before the vehicle enters the intersection,as well as the Circular Area to Collision(CATC)algorithm,which is used for secondary collision warning after the vehicle enters the intersection.This method compensates for the limitations of self-vehicle perception through networked information,improves detection efficiency through conflict area matching and safe distance filtering,and improves detection accuracy through dynamic distance difference threshold setting.The test results based on the NHTSA intersection scene set show that compared with the representative Time to Collision method and Time to Distance method,the false negative rate is reduced by 16%and 6%,and the false positive rate is reduced by 88%and 48%,respectively,and the detection time is reduced by about 74%,with higher accuracy and efficiency.
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