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车联网信息技术高速公路预警与应急避险模型
引用本文:刘海洋,冯仲科,吴云鹏,呼诺,冯泽邦.车联网信息技术高速公路预警与应急避险模型[J].交通运输系统工程与信息,2018,18(6):35-40.
作者姓名:刘海洋  冯仲科  吴云鹏  呼诺  冯泽邦
作者单位:1. 北京林业大学 精准林业北京市重点实验室,北京 100083;2. 北京交通大学轨道交通控制与安全国家重点实验室,北京 100044
基金项目:北京林业大学青年教师科学研究中长期项目/ Beijing Forestry University Young Teacher Science Research Medium and Long Term Project(2015ZCQ-LX-01);国家自然科学基金/ National Natural Science Foundation of China(U1710123);国家重点研发计划/ National Key Basic Research Program of China(2016YFB1200203).
摘    要:为减少高速公路车辆追尾和连环追尾等事故,本文研究了车联网信息技术高速公路预警与避险模型.本文利用车联网系统,将交通事故快速预报给后方车辆,并实时分析路面车辆信息,帮助后方车辆及时做出合理应急方案和应急措施.试验证明,跟车预警模型能够及时提醒驾驶人员避免追尾,在无法避免正面碰撞时,应急避险模型能够根据路面状况做出有效判断,成功进行避险,避免连环追尾事故发生.公路试验中第3车减少制动距离9.2 m,第4车减少制动距离21.4 m,较大地缩减事故后续车辆行车制动距离,能够在密集的行车路段,有效降低连环追尾事故的发生,提高高速公路交通运输安全.

关 键 词:公路运输  信息技术  车联网  公路预警  避险  跟车模型  
收稿时间:2018-07-09

Freeway Early Warning and Emergency Avoidance Model of the VANET Information Technology
LIU Hai-yang,FENG Zhong-ke,WU Yun-peng,HU Nuo,FENG Ze-bang.Freeway Early Warning and Emergency Avoidance Model of the VANET Information Technology[J].Transportation Systems Engineering and Information,2018,18(6):35-40.
Authors:LIU Hai-yang  FENG Zhong-ke  WU Yun-peng  HU Nuo  FENG Ze-bang
Institution:1. Beijing Key Laboratory of Precision Forestry, Beijing Forestry University, Beijing 100083, China; 2. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
Abstract:In order to reduce highway vehicle rear end collision and chain rear end collision, this paper studies the early warning and risk avoidance of the VANET information technology. This article uses the VANET information technology to quickly forecast the rear vehicles of traffic accidents, obtains and analyzes the information of the road vehicles according to the VANET information technology, and helps the rear vehicle drivers to make reasonable emergency plans in time and make emergency measures. The test proves that following the early warning model can prompt the driver to avoid rear-end collisions. When the traffic can not avoid frontal collision, the emergency hedging model can make effective judgments according to the road conditions, and successfully avoid the rear-end collision accident. In the highway test, the third vehicle reduced the braking distance by 9.2 m, and the fourth vehicle reduced the braking distance by 21.4 m, greatly reducing the vehicle braking distance of the accident follow-up vehicles. The accident can effectively reduce the occurrence of accidents such as rear-end collision in dense traffic lanes, and improve highway transportation safety.
Keywords:highway transportation  information technology  VANET  freeway early warning  risk avoidance  car-following model  
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