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An Omni-Directional Collision Warning Method Based on V2X Communication Technology
Technical Paper
2017-01-1990
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
The most important role of V2X technology is to significantly enhance driving safety. This paper proposes an Omni-directional collision warning method based on vehicle to vehicle communication. With the Basic Safety Message (BSM), the driving states of vehicles which communicate with host vehicle can be obtained. The warnings are divided into two categories based on the Lateral Offset calculation: forward collision warning (FCW) for vehicles moving in the same direction and cross collision warning (CCW) for vehicles moving in different directions. For vehicles which moves in the same direction, the lateral offset of the two vehicles, the time to collision (TTC) and time headway (THW) are used to estimate forward collision risk. For vehicles which moves in different directions, time to the closest point approach (TCPA) model and the separating axis theorem (SAT) are used for cross collision detection. With the methods above, nine applications are realized which include static vehicle reminding, slow vehicle reminding, close car-following distance reminding, forward collision warning, retrograde vehicle reminding, intersection collision warning, left-turn assist, entry of vehicle from auxiliary road reminding and collision inevitable warning. The effectiveness of the method is verified by a series of experiments on real roads. The factors that affect the Lateral Offset are analyzed. Compared to traditional methods, the danger detection rang are much wider and the danger in different directions can all be detected. It is worth mentioning that the effectiveness of the method relies on the accuracy of GPS positioning accuracy. The higher the GPS positioning accuracy is, the better the method works.
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Citation
huang, X. and Zhou, H., "An Omni-Directional Collision Warning Method Based on V2X Communication Technology," SAE Technical Paper 2017-01-1990, 2017, https://doi.org/10.4271/2017-01-1990.Data Sets - Support Documents
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