Abstract:Steering control for autonomous vehicles is used for more complex scenarios, such as nonlinear scenarios and varied vehicle speeds scenarios during the actual driving process. Model Predictive Control (MPC) is known as a feasible method for multi-constraints. However, a complicated mathematical model will lead to a great computational burden. To deal with this issue, a modified MPC-based adaptive steering strategy with nonlinear compensation by using Double Deep Q-learning Network Algorithm (DDQN) is proposed.… Show more
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