Velocity Planning for self-driving vehicles in a complex environment is one of the most challenging tasks. It must satisfy the following three requirements: safety with regards to collisions; respect of the maximum velocity limits defined by the traffic rules; comfort of the passengers. In order to achieve these goals, the jerk and dynamic objects should be considered, however, it makes the problem as complex as a non-convex optimization problem. In this paper, we propose a linear programming (LP) based velocity planning method with jerk limit and obstacle avoidance constraints for an autonomous driving system. To confirm the efficiency of the proposed method, a comparison is made with several optimization-based approaches, and we show that our method can generate a velocity profile which satisfies the aforementioned requirements more efficiently than the compared methods. In addition, we tested our algorithm on a real vehicle at a test field to validate the effectiveness of the proposed method.
翻译:复杂环境下自行驾驶车辆的速率规划是最具挑战性的任务之一,它必须满足以下三项要求:碰撞的安全性;遵守交通规则所规定的最大速度限制;乘客的舒适度。但是,为了实现这些目标,应当考虑自动和动态物体,但为了实现上述目标,它使问题像非电流优化问题一样复杂。在本文件中,我们提议一种基于直线编程的速度规划方法,配有自动驾驶系统的自动限制和障碍避免限制。为了确认拟议方法的效率,我们比较了几种基于优化的方法,我们表明我们的方法能够产生一种速度剖面,比比较方法更能满足上述要求。此外,我们还在试验场上测试了我们的真车算法,以验证拟议方法的有效性。