In this paper, a framework for the optimal longitudinal control of autonomous buses is proposed for multi-target scenarios. Autonomous buses operate on roads that present various events, such as vehicular interactions, traffic signals, and bus stop pauses. Consequently, the development of suitable acceleration/deceleration strategies and control systems that effectively respond to each situation is essential. For each event, a reference acceleration model is established. Priorities amongst numerous events are ascertained by comparing the reference accelerations designed for each situation. As for the longitudinal controller, a novel bus model is developed to embody the unique actuator characteristics inherent to large buses. Moreover, Model Predictive Control (MPC) is utilized to determine the optimal longitudinal acceleration for the selected target, enhancing passenger comfort by limiting acceleration and minimizing actuator transitions. The proposed longitudinal control system is validated through field tests in a complex road environment.


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    Title :

    Multi-target Longitudinal Control Based on Model Predictive Control for Autonomous Bus


    Additional title:

    Lect.Notes Mechanical Engineering


    Contributors:
    Huang, Wei (editor) / Ahmadian, Mehdi (editor) / Han, Sangwon (author) / Kim, Gihoon (author) / Choi, Jaeho (author) / Park, Geonyeong (author) / Choi, Seungwon (author) / Huh, Kunsoo (author)

    Conference:

    The IAVSD International Symposium on Dynamics of Vehicles on Roads and Tracks ; 2023 ; Ottawa, ON, Canada August 21, 2023 - August 25, 2023



    Publication date :

    2024-10-13


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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