An optimal trajectory planning algorithm for autonomous trucks: Architecture, algorithm, and experiment

Safe lane changing of the dynamic industrial park and port scenarios with autonomous trucks involves the problem of planning an effective and smooth trajectory. To solve this problem, we propose a new trajectory planning method based on the Dijkstra algorithm, which combines the Dijkstra algorithm with a cost function model and the Bezier curve. The cost function model is established to filter target trajectories to obtain the optimal target trajectory. The third-order Bezier curve is employed to smooth the optimal target trajectory. Road experiments are carried out with an autonomous truck to illustrate the effectiveness and smoothness of the proposed method. Compared with other conventional methods, the improved method can generate a more effective and smoother trajectory in the truck lane change.