A novel hierarchical model predictive control (MPC) method is investigated for four-wheel-independently-actuated (FWIA) autonomous ground vehicles (AGVs) with emergency collision avoidance in this paper, where an artificial potential field (APF)-based NMPC path replanner and a feedback compensation control (FCC)-based LTV-MPC path follower are designed. Both replanning with circle decomposition of vehicle shape, and tracking with tire force maximization, are considered simultaneously to enlarge the reachable zone of path replanning and following, particularly in much aggressive situations, where the trajectories are not feasible with the conventional approaches. By the proposed control, ample space and sufficient time are available to steer appropriately and acceleratelbrake independently in such hazardous scenarios. In addition, a shorter predictive horizon is introduced to evaluate both methods in more extreme situations. The simulations modeled in the Carsim-Simulink joint platform demonstrate that the proposed approach can further improve path-replanning reachability and path-following safety in emergency collision avoidance scenarios, even in a shortsighted prediction.


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    Title :

    An Integrated MPC Approach for FWIA Autonomous Ground Vehicles with Emergency Collision Avoidance


    Contributors:
    Cao, Mingcong (author) / Wang, Rongrong (author) / Wang, Jinxiang (author) / Chen, Nan (author)


    Publication date :

    2018-11-01


    Size :

    1665554 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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