Vehicle trajectory planning is a key component for an autonomous driving system. A practical system not only requires the component to compute a feasible trajectory, but also a comfortable one given certain comfort metrics. Nevertheless, computation efficiency is critical for the system to be deployed as a commercial product. In this paper, we present a novel trajectory planning algorithm based on nonlinear optimization. The algorithm computes a kinematically feasible and comfort-optimal trajectory that achieves collision avoidance with static obstacles. Furthermore, the algorithm is time efficient. It generates an 6-second trajectory within 10 milliseconds on an Intel i7 machine or 20 milliseconds on an Nvidia Drive Orin platform.

翻译：车辆轨迹规划是自动驾驶系统的关键组成部分。实用的系统不仅需要规划出可行轨迹，还要求在满足特定舒适度指标的前提下生成舒适轨迹。然而，计算效率对于系统实现商业化部署至关重要。本文提出了一种基于非线性优化的新型轨迹规划算法。该算法能够生成满足运动学可行性与舒适度最优且实现静态障碍物避碰的轨迹。此外，该算法具有高时效性：在Intel i7平台上生成6秒轨迹仅需10毫秒，在Nvidia Drive Orin平台上仅需20毫秒。