Prioritized CSMA Protocol for Roadside-to-Vehicle and Vehicle-to-Vehicle Communication Systems

Kosai, Jun; Kato, Seishiro; Saito, Toshiya; Matsugatani, Kazuoki; Nanba, Hideaki

doi:10.4271/2009-01-0165

Cited by 2 publications

(2 citation statements)

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“…At an early stage, the lower architecture of the V2V network has been studied related to the hardware and the protocol. [4][5][6] In the studies by Sauck 7 and Scwartz et al, 8 radio congestion control methods in the situation of dense surrounding vehicles were investigated. Also, studies on localization were performed where the position correction messages via V2V communication were used to increase the accuracy of the relative position measurements.…”

Section: Introductionmentioning

confidence: 99%

“…This includes the distance and the direction of the RVs, the occupying lanes and the highway exit and merge. Even when the communication and safety application layers in Figure 1 have been actively studied and reported, [3][4][5][6][7][8][9][10][11][12] the classification layer between those layers is not well addressed in the related literature.…”

Section: Introductionmentioning

confidence: 99%

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Target classification layer design via vehicle-to-vehicle communication

Kim

Park

Huh

2016

Proceedings of the Institution of Mechanical Engineers, Part D:

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Recently, an active safety system based on vehicle-to-vehicle communication was introduced to minimize the threat of car accidents on the road and to overcome the limitations of the current sensor-based advanced driver assist system. In order to implement the system based on vehicle-to-vehicle communication, target classification is the key layer to be developed. In this study, based on the transmitted path history of the remote vehicles, the road geometry around the host vehicle is reconstructed without in-vehicle sensors such as vision cameras. A tracking algorithm for the remote vehicle is formulated in order to predict its position continuously by using an extended Kalman filter. A local map is obtained with an outlier filter, and the target classification algorithm is designed from vehicle-to-vehicle communication data. The proposed algorithms are validated by simulations and experiments carried out using test vehicles.

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