Parallel, Angular and Perpendicular Parking for Self-Driving Cars using Deep Reinforcement Learning
parking是所有驾驶行为的最终步骤,主要分为三类:垂直、平行、斜向泊车。
本文使用DDPG控制汽车完成三种场景的泊车。
1 Introduction
- 强化学习控制泊车:
- "Reinforcement learning-based end-to-end parking for automatic parking system", Sensors (Switzerland), vol. 19 ,September 2019.
- “An Automatic Parking Model Based on Deep Reinforcement Learning", 2021 J. Phys.: Conf. Ser. 1883 012111.
- parallel autonomous parking (truncated Monte Carlo tree):
- “Data efficient reinforcement learning for integrated lateral planning and control in automated parking system”, Sensors (Switzerland), vol. 20, pp. 1–24, dec 2020.
- "Reinforcement Learning-Based Motion Planning for Automatic Parking System," in IEEE Access, vol. 8, pp. 154485-154501, 2020, doi: 0.1109/ACCESS.2020.3017770.
- 避障:
- "Q-Learning for Autonomous Mobile Robot Obstacle Avoidance," 2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), Porto, Portugal, 2019, pp. 1-7. DOI: 10.1109/ICARSC.2019.8733621
- Combining YOLO and Deep Reinforcement Learning for Autonomous Driving in Public Roadworks Scenarios. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-547-0, pages 793-800. DOI: 10.5220/0010913600003116.
总结
本文除了比较新之外(2022)没有无亮点,完全借用DDPG分别实现三种库的parking