Parameter effects of the potential-field-driven model predictive control(pf-mpc)method on performances of shared control systems during obstacles avoidance are *** pf-mpc controllers of autonomous driving and shared c...
详细信息
Parameter effects of the potential-field-driven model predictive control(pf-mpc)method on performances of shared control systems during obstacles avoidance are *** pf-mpc controllers of autonomous driving and shared control systems are designed based on the constructed potential fields and model predictive control method,and the driver-vehicle dynamics and the driver-related costs are also considered in the design of the shared *** explore a potential approach of alleviating driver-automation conflicts of the shared control systems,different motion planning results generated by the pf-mpc controller are explored by adjusting effects of potential fields’parameters,which provides possibilities to decrease driver-automation conflicts between the planned trajectory and driver’s target ***,two case studies are designed to discuss different frameworks and parameters effects on shared control *** show that the proposed shared control frameworks considering driver-vehicle dynamics and the driver-related cost show better performances regarding driver-automation conflicts management and driving safety than the decentralized control *** the longitudinal normalized constant of potential fields parameters shows influences on the driver-automation conflicts management and driving safety performances of shared control.
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