Smooth and safe speed planning is imperative for the successful deployment of autonomous vehicles. This paper presents a mathematical formulation for the optimal speed planning of autonomous driving, which has been validated in high-fidelity simulations and real-road demonstrations with practical constraints. The algorithm explores the inter-traffic gaps in the time and space domain using a breadth-first search. For each gap, quadratic programming finds an optimal speed profile, synchronizing the time and space pair along with dynamic obstacles. Qualitative and quantitative analysis in Carla is reported to discuss the smoothness and robustness of the proposed algorithm. Finally, we present a road demonstration result for urban city driving.

翻译：平滑且安全的速度规划对于自动驾驶车辆的成功部署至关重要。本文提出一种面向自动驾驶最优速度规划的数学形式化方法，该方法已通过高保真仿真验证及考虑实际约束的真实道路演示。算法采用广度优先搜索在时空域中探索交通间隙。针对每个间隙，二次规划算法求解最优速度剖面，实现与动态障碍物间的时空协同。通过Carla仿真环境中的定性与定量分析，讨论了所提算法的平滑性与鲁棒性。最后，给出了城市道路环境的实际驾驶演示结果。