Human-Machine Cooperative Control of Intelligent Vehicles Considering the Trajectory Tracking Accuracy and Driver Load

Aiming at improving the trajectory tracking accu-racy, reducing driver load and human-machine conflict during human-machine driving, this paper designs an intelligent vehicles human-machine cooperative controller considering the trajectory tracking accuracy and driver load. A human-machine cooperative controller is designed based on the interactive cooperative control outputs. The controller can respond to the driver's output in real time, and a parallel indirect cooperative control structure is formed with the controller and the driver model. To solve the flexibility of weight allocation for man-machine driving, a weight distributor is designed based on the fuzzy theory considering the fuzzy inputs of the driver's output, lateral deviation and lateral velocity. The proposed human-machine cooperative method is verified by the CarSimlSimulink platform. The results show that the cooperative controller and weight allocation method can effectively improve the trajectory tracking accuracy, and reduce the driver load and human-machine conflict.