![](/images/graphics-bg.png)
A Sarsa(λ)-Based Control Model for Real-Time Traffic Light Coordination
Joint Authors
Zhu, Fei
Liu, Quan
Huang, Wei
Zhou, Xiaoke
Fu, Yuchen
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-23
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road.
Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control.
Each junction wants to get larger traffic flow.
During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests.
A good traffic signal timing policy is helpful to solve the problem.
However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution.
The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow.
Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy.
The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively.
The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions.
The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.
American Psychological Association (APA)
Zhou, Xiaoke& Zhu, Fei& Liu, Quan& Fu, Yuchen& Huang, Wei. 2014. A Sarsa(λ)-Based Control Model for Real-Time Traffic Light Coordination. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1050943
Modern Language Association (MLA)
Zhou, Xiaoke…[et al.]. A Sarsa(λ)-Based Control Model for Real-Time Traffic Light Coordination. The Scientific World Journal No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-1050943
American Medical Association (AMA)
Zhou, Xiaoke& Zhu, Fei& Liu, Quan& Fu, Yuchen& Huang, Wei. A Sarsa(λ)-Based Control Model for Real-Time Traffic Light Coordination. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1050943
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1050943