Algorithm Based on Cooperative Vehicle Infrastructure Systems

In order to determine the problem of vehicle positioning deviation caused by a lack and delay of the positioning signal, a cooperative map-matching（CMM）algorithm, based on the cooperative vehicle infrastructure system, is proposed in this paper. First, the information obtained by GPS and that obtained by vehicular dead reckoning（DR）were fused to obtain the initial position of cooperative map-matching using an extended Kalman filter（EKF）. Then, vehicle information was exchanged and shared based on dedicated short-range communication （DSRC）. On the basis of an electronic map, the further positioning of vehicles was accomplished using road constraints. In order to verify the effectiveness of the proposed algorithm, an environment to simulate real scenes was set up to conduct the experiments. The experimental results demonstrate that the average positioning deviation of vehicles at intersections using EKF, which fuses data obtained from GPS and DR, is 9.90 m. The positioning deviation decreased by 30.87%, when compared with the average deviation of GPS, which is 14.31 m. The proposed CMM algorithm has an average position deviation of 4.5 m when the number of vehicles involved is 7, and 2.75 m when the number of vehicles involved is 10. The positioning deviation decreased by 69.74%.