To enable autonomous vehicles to perform discretionary 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. Additionally, A long-short term memory (LSTM) model is used to predict the trajectories of surrounding vehicles for both the MPC decision and control modules. The proposed lane-change decision and control method is simulated and validated in a driving simulator under random highway traffic conditions.


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    Title :

    Highway Discretionary Lane-Change Decision and Control Using Model Predictive Control


    Contributors:
    Zheng, Zishun (author) / Wang, Yihan (author) / Lin, Yuan (author)


    Publication date :

    2024-07-05


    Size :

    239787 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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