Car-following method based on inverse reinforcement learning for autonomous vehicle decision-making
There are still some problems need to be solved though there are a lot of achievements in the fields of automatic driving. One of those problems is the difficulty of designing a car-following decision-making system for complex traffic conditions. In recent years, reinforcement learning shows the pot...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2018-12-01
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| Series: | International Journal of Advanced Robotic Systems |
| Online Access: | https://doi.org/10.1177/1729881418817162 |
| _version_ | 1818403883850924032 |
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| author | Hongbo Gao Guanya Shi Guotao Xie Bo Cheng |
| author_facet | Hongbo Gao Guanya Shi Guotao Xie Bo Cheng |
| author_sort | Hongbo Gao |
| collection | DOAJ |
| description | There are still some problems need to be solved though there are a lot of achievements in the fields of automatic driving. One of those problems is the difficulty of designing a car-following decision-making system for complex traffic conditions. In recent years, reinforcement learning shows the potential in solving sequential decision optimization problems. In this article, we establish the reward function R of each driver data based on the inverse reinforcement learning algorithm, and r visualization is carried out, and then driving characteristics and following strategies are analyzed. At last, we show the efficiency of the proposed method by simulation in a highway environment. |
| first_indexed | 2024-12-14T08:31:20Z |
| format | Article |
| id | doaj.art-44253443375943bfb04b314e9670e52c |
| institution | Directory Open Access Journal |
| issn | 1729-8814 |
| language | English |
| last_indexed | 2024-12-14T08:31:20Z |
| publishDate | 2018-12-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | International Journal of Advanced Robotic Systems |
| spelling | doaj.art-44253443375943bfb04b314e9670e52c2022-12-21T23:09:30ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142018-12-011510.1177/1729881418817162Car-following method based on inverse reinforcement learning for autonomous vehicle decision-makingHongbo Gao0Guanya Shi1Guotao Xie2Bo Cheng3 Center for Intelligent Connected Vehicles and Transportation, Tsinghua University, Beijing, China Electrical Engineering Department, California Institute of Technology, Pasadena, CA, USA Department of Automotive Engineering, Hunan University, Changsha, Hunan, China State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, ChinaThere are still some problems need to be solved though there are a lot of achievements in the fields of automatic driving. One of those problems is the difficulty of designing a car-following decision-making system for complex traffic conditions. In recent years, reinforcement learning shows the potential in solving sequential decision optimization problems. In this article, we establish the reward function R of each driver data based on the inverse reinforcement learning algorithm, and r visualization is carried out, and then driving characteristics and following strategies are analyzed. At last, we show the efficiency of the proposed method by simulation in a highway environment.https://doi.org/10.1177/1729881418817162 |
| spellingShingle | Hongbo Gao Guanya Shi Guotao Xie Bo Cheng Car-following method based on inverse reinforcement learning for autonomous vehicle decision-making International Journal of Advanced Robotic Systems |
| title | Car-following method based on inverse reinforcement learning for autonomous vehicle decision-making |
| title_full | Car-following method based on inverse reinforcement learning for autonomous vehicle decision-making |
| title_fullStr | Car-following method based on inverse reinforcement learning for autonomous vehicle decision-making |
| title_full_unstemmed | Car-following method based on inverse reinforcement learning for autonomous vehicle decision-making |
| title_short | Car-following method based on inverse reinforcement learning for autonomous vehicle decision-making |
| title_sort | car following method based on inverse reinforcement learning for autonomous vehicle decision making |
| url | https://doi.org/10.1177/1729881418817162 |
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