Evaluation and Application of Urban Traffic Signal Optimizing Control Strategy Based on Reinforcement Learning
Joint Authors
Yang, Xiaoguang
Wang, Yizhe
Liang, Hailun
Liu, Yangdong
Source
Journal of Advanced Transportation
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-26
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Reinforcement learning method has a self-learning ability in complex multidimensional space because it does not need accurate mathematical model and due to the low requirement for prior knowledge of the environment.
The single intersection, arterial lines, and regional road network of a group of multiple intersections are taken as the research object on the paper.
Based on the three key parameters of cycle, arterial coordination offset, and green split, a set of hierarchical control algorithms based on reinforcement learning is constructed to optimize and improve the current signal timing scheme.
However, the traffic signal optimization strategy based on reinforcement learning is suitable for complex traffic environments (high flows and multiple intersections), and the effects of which are better than the current optimization methods in the conditions of high flows in single intersections, arteries, and regional multi-intersection.
In a word, the problem of insufficient traffic signal control capability is studied, and the hierarchical control algorithm based on reinforcement learning is applied to traffic signal control, so as to provide new ideas and methods for traffic signal control theory.
American Psychological Association (APA)
Wang, Yizhe& Yang, Xiaoguang& Liu, Yangdong& Liang, Hailun. 2018. Evaluation and Application of Urban Traffic Signal Optimizing Control Strategy Based on Reinforcement Learning. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1181160
Modern Language Association (MLA)
Wang, Yizhe…[et al.]. Evaluation and Application of Urban Traffic Signal Optimizing Control Strategy Based on Reinforcement Learning. Journal of Advanced Transportation No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1181160
American Medical Association (AMA)
Wang, Yizhe& Yang, Xiaoguang& Liu, Yangdong& Liang, Hailun. Evaluation and Application of Urban Traffic Signal Optimizing Control Strategy Based on Reinforcement Learning. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1181160
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181160