Motion planning for intersection turning of heavy-duty autonomous vehicles using vehicle body trajectory prediction and risk potential evaluation - Yutaka HAMAGUCHI; Yo SANOGAWA; Pongsathorn RAKSINCHAROENSAK (Nihon Kikai Gakkai ronbunshu, 2023)
The shortage of drivers for trucks and buses has become a critical problem in recent years, leading to active research and development on unmanned and manpower-saving operation of heavy-duty vehicles. However, due to their larger overhangs compared to passenger cars, heavy-duty vehicles are more difficult to maneuver on narrow roads and sharp curves, especially those commonly found in urban areas or parking lots. Consequently, path tracking control systems commonly applied to passenger cars cannot be directly used for heavy-duty vehicles. Thus, the objective of this study is to develop a path planning and motion control system for autonomous driving of heavy-duty vehicles on roads with large curvatures. To design the control system, a risk potential is utilized to express the driver's sense of danger towards obstacles and road boundaries. Simulations are conducted on a course that replicates an actual intersection, and a parameter study is carried out. Finally, the simulation results of this approach are compared with those of a conventional path-following method. The results demonstrate that the proposed method is effective for obstacle avoidance in intersection situations.