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Many vehicular safety applications rely on vehicles periodically broadcasting their position information and location trace. In very dense networks, such safety messaging can lead to offered traffic loads that saturate the shared wireless medium. One approach to address this problem is to reduce the frequency of location update messages when the movements of a vehicle can be predicted by nearby vehicles. In this paper, the authors study how predictable vehicular locations are, given a Global Positioning System trace of a vehicles recent path. They empirically evaluate the performance of linear and higher degree polynomial prediction algorithms using about 2500 vehicle traces collected under urban and highway driving conditions.
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