On the Importance of Accurate Relative Motion Models for Target Vehicle Trajectory Tracking

Models from the literature that have previously been utilized for target vehicle tracking typically contain vehicle motion equations described in inertial coordinate systems. Using these inertial models to track the trajectories of target vehicles in a rotating or accelerating sensor coordinate system, such as a coordinate frame attached to a turning ego vehicle, requires knowledge of the absolute location and accurate orientation of the ego vehicle itself in the inertial coordinate system. However, accurately obtaining these ego variables is not only challenging, but also needs expensive sensors and extra computational resources. To bypass this process in certain applications such as collision warning detection, this paper develops a novel trajectory tracking model that describes the relative motion of target vehicles in the frame attached to the ego vehicle. Unlike traditional models, this relative trajectory model is more accurate and only requires knowledge of the velocity and yaw rate of the ego vehicle, which are easier to obtain compared to position and orientation. Simulation and experimental findings demonstrate that the relative model can effectively replace traditional models in vehicle tracking, proving to be more accurate when the ego-vehicle has non-zero steering and advantageous in scenarios where vehicle position and orientation data are unavailable.