The vehicle collision warning on urban road based on internet of vehicles data

被引：0
作者：
Chen W.S. [1 ,2 ]
Zhou Z.G. [2 ]
Tuo L.F. [3 ]
Lin J.X. [2 ]
机构：
[1] College of Architectural and Civil Engineering, Guangzhou Panyu Polytechnic, Guangzhou
[2] Department of Research and Development, Dragon Spring Technology Co., Ltd, Guangzhou
[3] School of Economics and Management, Guangzhou College of Applied Science and Technology, Guangzhou
来源：
Advances in Transportation Studies | 2022年 / 4卷 / Special issue期
关键词：
Internet of vehicles data; Kalman filter; Safe distance model; Urban road; Vehicle collision warning;
D O I：
10.53136/97912218027641
中图分类号：
学科分类号：
摘要：
It is of great significance to provide early warning for vehicle collisions on urban roads. In order to overcome the high missing rate and low warning accuracy and poor efficiency of traditional early warning methods, an urban road vehicle collision early warning method based on Internet of Vehicles data was proposed. The extended Kalman filter is used to estimate the vehicle attitude on urban roads, and the vehicle longitudinal safety distance model is established. Based on the Internet of Vehicles, the position, speed, acceleration and heading information of follow-up vehicles on urban roads and vehicles in front of urban roads are obtained, and the dispersion of vehicle spacing changes is obtained. The dispersion isused as the judgment threshold of urban road vehicle collision warning to realize collision warning. The experimental results show that the average false alarm rate is 1.2%, the maximum false alarm rate is only 1%, and the alarm time is only 19.9s. © 2022, Aracne Editrice. All rights reserved.
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页码：3 / 12
页数：9
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