Forward search algorithm based on dynamic programming for real-time adaptive traffic signal control

The scheduling of traffic signal at intersections is involved in an application of artificial intelligence system. This study presents a new forward search algorithm based on dynamic programming (FSDP) under a decision tree, and explores an efficient solution for real-time adaptive traffic signal co...

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Veröffentlicht in:IET intelligent transport systems Jg. 9; H. 7; S. 754 - 764
Hauptverfasser: Yin, Biao, Dridi, Mahjoub, El Moudni, Abdellah
Format: Journal Article
Sprache:Englisch
Veröffentlicht: The Institution of Engineering and Technology 01.09.2015
Institution of Engineering and Technology
Schlagworte:
adaptive control
Algorithms
artificial intelligence
artificial intelligence system
asymmetrical traffic flow scenarios
Computer Science
decision tree
decision trees
Dynamic programming
fixed phase sequence
forward research dynamic programming
forward search algorithm
FSDP algorithm
labelled position method
Mathematical models
Mathematics
online algorithm
optimal control
optimal fixed‐time control
Optimization
Policies
process optimisation
real‐time adaptive traffic signal control policy
road traffic control
rolling horizon approach
scheduling
search problems
traffic delay evaluation
Traffic engineering
Traffic flow
traffic signal scheduling
Traffic signals
variable phase sequence
fixed phase sequence
process optimisation
traffic signal scheduling
artificial intelligence system
forward research dynamic programming
road traffic control
online algorithm
dynamic programming
adaptive control
optimal control
labelled position method
rolling horizon approach
artificial intelligence
FSDP algorithm
decision tree
variable phase sequence
asymmetrical traffic flow scenarios
optimal fixed-time control
decision trees
forward search algorithm
scheduling
traffic delay evaluation
real-time adaptive traffic signal control policy
search problems
ISSN:1751-956X, 1751-9578
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Beschreibung
Zusammenfassung:The scheduling of traffic signal at intersections is involved in an application of artificial intelligence system. This study presents a new forward search algorithm based on dynamic programming (FSDP) under a decision tree, and explores an efficient solution for real-time adaptive traffic signal control policy. Traffic signal control with cases of fixed phase sequence and variable phase sequence are both considered in the algorithm. Owing to the properties of forward research dynamic programming and the process optimisation of repeated or invalid traffic states the authors proposed, FSDP algorithm reduces the number of states and saves much computation time. Consequently, FSDP is certain to be an on-line algorithm through its application to a complicated traffic control problem. Moreover, the labelled position method is firstly proposed in the author's study to search the optimal policy after reaching the goal state. For practical operations, this new algorithm is extended by adding the rolling horizon approach, and some derived methods are compared with the optimal fixed-time control and adaptive control on the evaluation of traffic delay. Experimental results obtained by the simulations of symmetrical and asymmetrical traffic flow scenarios show that the FSDP method can perform quite well with high efficiency and good qualities in traffic control.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1751-956X
1751-9578
DOI:10.1049/iet-its.2014.0156