Reinforcement Learning Ramp Metering without Complete Information
Joint Authors
Xi, Xiao-Ming
Wang, Xing-Ju
Gao, Gui-Feng
Source
Journal of Control Science and Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-03-05
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Electronic engineering
Information Technology and Computer Science
Abstract EN
This paper develops a model of reinforcement learning ramp metering (RLRM) without complete information, which is applied to alleviate traffic congestions on ramps.
RLRM consists of prediction tools depending on traffic flow simulation and optimal choice model based on reinforcement learning theories.
Moreover, it is also a dynamic process with abilities of automaticity, memory and performance feedback.
Numerical cases are given in this study to demonstrate RLRM such as calculating outflow rate, density, average speed, and travel time compared to no control and fixed-time control.
Results indicate that the greater is the inflow, the more is the effect.
In addition, the stability of RLRM is better than fixed-time control.
American Psychological Association (APA)
Wang, Xing-Ju& Xi, Xiao-Ming& Gao, Gui-Feng. 2012. Reinforcement Learning Ramp Metering without Complete Information. Journal of Control Science and Engineering،Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-454651
Modern Language Association (MLA)
Wang, Xing-Ju…[et al.]. Reinforcement Learning Ramp Metering without Complete Information. Journal of Control Science and Engineering No. 2012 (2012), pp.1-8.
https://search.emarefa.net/detail/BIM-454651
American Medical Association (AMA)
Wang, Xing-Ju& Xi, Xiao-Ming& Gao, Gui-Feng. Reinforcement Learning Ramp Metering without Complete Information. Journal of Control Science and Engineering. 2012. Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-454651
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-454651