A Gaussian Process Model for Opponent Prediction in Autonomous Racing
Edward L. Zhu,Finn Lukas Busch,Jake Johnson,Francesco Borrelli,Edward L. Zhu,Finn Lukas Busch,Jake Johnson,Francesco Borrelli
In head-to-head racing, performing tightly con-strained, but highly rewarding maneuvers, such as overtaking, require an accurate model of interactive behavior of the opposing target vehicle (TV). We propose to construct a prediction model given data of the TV from previous races. In particular, a one-step Gaussian process (GP) model is trained on closed-loop interaction data to learn the behavior ...
