To enable vehicles to perform automatic lane change amidst the random traffic flow on highways, this paper introduces a decision-making and control method for vehicle lane-change based on Model Predictive Control (MPC). This approach divides the driving control of vehicles on highways into two parts: lane-change decision and lane-change control, both of which are solved using the MPC method. In the lane-change decision module, the minimum driving costs for each lane are computed and compared by solving the MPC problem to make lane-change decisions. In the lane-change control module, a dynamic bicycle model is incorporated, and a multi-objective cost function is designed to obtain the optimal control inputs for the lane-change process. The proposed lane-change decision and control methods are simulated and validated within the SUMO platform under random highway traffic conditions.
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Zheng et al. (2024) studied this question.
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