Long-term prediction of vehicle trajectory based on a deep neural network

Abstract

Accurate prediction of the future locations of the host vehicle as well as that of the surrounding objects is one of the key challenges in improving road traffic safety. The traditional approach for this task has been using physics-based motion models such as kinematic and dynamic models, the result of which is not reliable for long-term prediction. In this paper, we present simulation results demonstrating the effectiveness of employing a deep neural network (DNN) for vehicle trajectory prediction. The DNN is trained to output the trajectory of the vehicle for the following few seconds.