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Self-driving Car Navigation with Obstacle Avoidance Using Reinforcement Learning
| 题名： | Self-driving Car Navigation with Obstacle Avoidance Using Reinforcement Learning |
| 正文语种： | 中文 |
| 作者： | Fang Xiao Chen Xiaohua Gao Hongbo Yang Ming |
| 作者单位： | hery Scientific Research Institute;Shanghai Jiao Tong University hery Scientific Research Institute hery Scientific Research Institute;Nanjing University of Science & Technology Shanghai Jiao Tong University 4 |
| 关键词： | reinforcement learning car navigation obstacle avoidance adaptive dynamic programming reinforcement signal |
| 摘要： | Self-driving car navigation with obstacle avoidance problem is a hot topic in academic world.The goal of this problem is to design an autonomous car with learning ability to find a collision-free path in an unknown environment.General solutions to this problem could be divided into two pieces,navigation environment detection and control strategy design.In this paper,we used reinforcement learning(RL)to approach control strategy design and built two different navigation benchmarks with different obstacles situations to verify the control strategy.The simulation results showed that the RL provides an effective solution to self-driving car navigation with obstacles avoidance problem. |
| 会议日期： | 201510 |
| 会议举办地点： | 上海 |
| 会议名称： | 2015中国汽车工程学会年会 |
| 出版日期： | 2015-09-30 |
| 母体文献： | 2015中国汽车工程学会年会论文集 |
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