Motion Planning Methodologies for Automated Vehicles: A Critical Review - LI Bai; ZHANG Youmin; SHAO Zhijiang (Kongzhi Yu Xinxi Jishu)
Decision-making module in automated vehicle system is responsible for generating the driving behaviors of the automated vehicle, thus being a critical and direct reflection of the intelligence level of the whole system. The decision-making module usually consists of several layers. Among them, motion planning, responsible for partial trajectory generation, is the most critical factor that affects the driving quality. This article reviewed the Chinese references about motion planning in recent years, and classified them as curve-based, sample-based, learning-based and optimization-based categories. The advantages and disadvantages of each category were discussed in details. As the trend, the methods from different categories would integrate so as to strengthen the capability in dealing with real-world demands. Issues such as vehicle kinematic model formulation, environment description, fault-recovery strategy design, solution space reduction and solution unification deserve further investigations in the future.