| Item type |
Symposium(1) |
| 公開日 |
2019-11-04 |
| タイトル |
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タイトル |
Evaluation of an Adaptive Traffic Control Algorithm Based on Back-Pressure and Q-Learning |
| タイトル |
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言語 |
en |
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タイトル |
Evaluation of an Adaptive Traffic Control Algorithm Based on Back-Pressure and Q-Learning |
| 言語 |
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言語 |
eng |
| 資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_5794 |
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資源タイプ |
conference paper |
| 著者所属 |
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Division of Information Science Nara Institute of Science and Technology |
| 著者所属 |
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Division of Information Science Nara Institute of Science and Technology |
| 著者所属 |
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Division of Information Science Nara Institute of Science and Technology |
| 著者所属 |
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Division of Information Science Nara Institute of Science and Technology |
| 著者所属(英) |
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en |
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Division of Information Science Nara Institute of Science and Technology |
| 著者所属(英) |
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en |
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Division of Information Science Nara Institute of Science and Technology |
| 著者所属(英) |
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en |
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Division of Information Science Nara Institute of Science and Technology |
| 著者所属(英) |
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en |
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Division of Information Science Nara Institute of Science and Technology |
| 著者名 |
Maipradit, Arnan
Kawakami, Tomoya
Gao, Juntao
Ito, Minoru
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| 著者名(英) |
Arnan, Maipradit
Tomoya, Kawakami
Juntao, Gao
Minoru, Ito
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| 論文抄録 |
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内容記述タイプ |
Other |
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内容記述 |
Traffic congestion causes significant problems such as longer travel time, energy consumption, and air pollution. Currently, we have proposed an adaptive traffic control algorithm based on back-pressure and Q-learning to efficiently reduce congestion. In this paper, we evaluate our proposed method using the road network simulated by a real structure. The simulation results show that our algorithm significantly decreases average vehicle traveling time from 17% to 37% compared with the state-of-the-art algorithm. |
| 論文抄録(英) |
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内容記述タイプ |
Other |
|
内容記述 |
Traffic congestion causes significant problems such as longer travel time, energy consumption, and air pollution. Currently, we have proposed an adaptive traffic control algorithm based on back-pressure and Q-learning to efficiently reduce congestion. In this paper, we evaluate our proposed method using the road network simulated by a real structure. The simulation results show that our algorithm significantly decreases average vehicle traveling time from 17% to 37% compared with the state-of-the-art algorithm. |
| 書誌情報 |
第27回マルチメディア通信と分散処理ワークショップ論文集
p. 274-276,
発行日 2019-11-04
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| 出版者 |
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言語 |
ja |
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出版者 |
情報処理学会 |
IPSJ-DPSWS2019045.pdf (306.4 kB)
