This thesis presents the formulation and validation of tracking algorithms for vehicular motion for use in active collision prevention in V2V communications. The main objective is to estimate position and velocity of a vehicle based on update from vehicular wireless network. By using vehicular wireless network, the range of position estimation improves when compare to conventional radars and sensors. On the other hand, from a vehicular wireless network point of view regular measurement information update is more difficult to obtain because of packet losses due to interference between communicating vehicles. Our proposed algorithms are based on methods from position tracking termed alpha-beta trackers in aerospace applications with constant rate of information updates, with some modifications to better solve the problem. We present the main algorithms and provide numerical evidence of their accuracy based on simulation data. The modified filters are shown to be computationally efficient (lightweight) and provide sufficient accuracy for estimation of vehicle positions based on information update in a wireless V2V system.

This thesis presents the formulation and validation of tracking algorithms for vehicular motion for use in active collision prevention in V2V communications. The main objective is to estimate position and velocity of a vehicle based on update from vehicular wireless network. By using vehicular wireless network, the range of position estimation improves when compare to conventional radars and sensors. On the other hand, from a vehicular wireless network point of view regular measurement information update is more difficult to obtain because of packet losses due to interference between communicating vehicles. Our proposed algorithms are based on methods from position tracking termed alpha-beta trackers in aerospace applications with constant rate of information updates, with some modifications to better solve the problem. We present the main algorithms and provide numerical evidence of their accuracy based on simulation data. The modified filters are shown to be computationally efficient (lightweight) and provide sufficient accuracy for estimation of vehicle positions based on information update in a wireless V2V system.