Continuous optimization based motion planners require deciding on a maneuver homotopy before optimizing the trajectory. Under uncertainty, maneuver intentions of other participants can be unclear, and the vehicle might not be able to decide on the most suitable maneuver. This work introduces a method that incorporates multiple maneuver preferences in planning. It optimizes the trajectory by considering weighted maneuver preferences together with uncertainties ranging from perception to prediction while ensuring the feasibility of a chance-constrained fallback option. Evaluations in both driving experiments and simulation studies show enhanced interaction capabilities and comfort levels compared to conventional planners, which consider only a single maneuver.

翻译：基于连续优化的运动规划器需要在优化轨迹前决定操作同伦。在不确定性条件下，其他参与者操作意图可能不明确，车辆难以决定最合适的操作。本研究提出一种在规划中融合多种操作偏好的方法。该方法通过考虑加权操作偏好以及从感知到预测的不确定性来优化轨迹，同时确保机会约束后备方案的可行性。驾驶实验与仿真研究的评估表明，与仅考虑单一操作的传统规划器相比，该方法增强了交互能力与舒适度水平。