Optimal Cooperative Path Planning Considering Driving Intention for Shared Control

This paper presents an optimal cooperative path planning method considering driver’s driving intention for shared control to address target path conflicts during the driver-automation interaction by using the convex optimization technique based on the natural cubic spline. The optimal path criteria (e.g. the optimal curvature, the optimal heading angle) are formulated as quadratic forms using the natural cubic spline, and the initial cooperative path profiles of the cooperative path in the Frenet-based coordinate system are induced by considering the driver’s lane-changing intention recognized by the Support Vector Machine (SVM) method. Then, the optimal cooperative path could be obtained by the convex optimization techniques. The noncooperative game theory is adopted to model the driver-automation interaction in this shared control framework, where the Nash equilibrium solution is derived by the model predictive control (MPC) approach. Finally, the proposed framework is tested with different driver’s driving intentions to avoid obstacles on a straight road and a curvy road. As a result, the planned path could continuously adapt to the driving intention and various road shapes, and the path conflicts between the human driver and the controller is also decreased by the proposed cooperative path planning method in the game-based shared control framework.