To address the driving conflicts of connected automated vehicles(CAVs)at unsignalized roundabouts,a cooperative decision-making framework is proposed.The personalized driving preferences of CAVs are considered in the ...To address the driving conflicts of connected automated vehicles(CAVs)at unsignalized roundabouts,a cooperative decision-making framework is proposed.The personalized driving preferences of CAVs are considered in the decision-making algorithm,which are reflected by different driving styles.A motion prediction algorithm is used to improve the decision-making performance.The effect of the motion prediction algorithm on the decisionmaking performance is evaluated,including the advancement of driving safety and the computational load for the hardware.The cooperative game theoretic approach is applied to the interaction modelling and collaborative decision making of CAVs.Finally,hardware-in-the-loop(HIL)tests are carried out to evaluate the feasibility and real-time performance of the proposed algorithm.展开更多
基金A*STAR,Singapore,under Grant SERC 1922500046 and Grant A2084c0156the SUG-NAP,Nanyang Technological University,under Grant M4082268.050.
文摘To address the driving conflicts of connected automated vehicles(CAVs)at unsignalized roundabouts,a cooperative decision-making framework is proposed.The personalized driving preferences of CAVs are considered in the decision-making algorithm,which are reflected by different driving styles.A motion prediction algorithm is used to improve the decision-making performance.The effect of the motion prediction algorithm on the decisionmaking performance is evaluated,including the advancement of driving safety and the computational load for the hardware.The cooperative game theoretic approach is applied to the interaction modelling and collaborative decision making of CAVs.Finally,hardware-in-the-loop(HIL)tests are carried out to evaluate the feasibility and real-time performance of the proposed algorithm.
