Decentralized motion planning for intelligent bus platoon based on hierarchical optimization framework

Intelligent bus platoon effectively meets the high demand for public transport during rush hours. A decentralized motion planning method based on hierarchical optimization framework is proposed for intelligent bus platoon to improve flexibility and efficiency. This method realizes the optimization of the guidance trajectory in the higher layer, and the optimization of the motion trajectory in the lower layer. First, a guidance trajectories generation method is presented to decouple the platoon motion planning. The state and trajectory of the preceding bus are used as a reference to constrain the lateral and longitudinal feasible space for the current bus. Meanwhile, the quintic polynomial is adopted to generate the trajectory cluster and the optimal trajectory is selected using the multi-objective optimization. Second, the joint kinematics model of the bus is built as the prediction model. And independent model predictive control modules are utilized to optimize each guidance trajectory to make them smoother and safer. The obstacle avoidance constraints are reconstructed based on the duality theorem. Finally, simulations demonstrate the advantages of the decentralized motion planning method under different scenarios, and results demonstrate our method improves the flexibility and consistency of the platoon.