Multiple traffic signal control using a GA.

Kalganova, Tatiana, Russell, Gordon and Cumming, Andrew (1999) Multiple traffic signal control using a GA. In: Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Portorož, Slovenia, 1999. Springer-Verlag, pp. 220-228. ISBN 978-3-211-83364-3

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Optimising traffic signal timings for a multiple-junction road
network is a difficult but important problem. The essential difficulty
of this problem is that the traffic signals need to coordinate
their behaviours to achieve the common goal of optimising
overall network delay. This paper discusses a novel
approach towards the generation of optimal signalling strategies,
based on the use of a genetic algorithm (GA). This GA
optimises the set of signal timings for all junctions in network.
The different efficient red and green times for all the signals are
determined by genetic algorithm as well as the offset time for
each junction. Previous attempts to do this rely on a fixed cycle
time, whereas the algorithm described here attempts to optimise
cycle time for each junction as well as proportion of green
times. The fitness function is a measure of the overall delay of
the network. The resulting optimised signalling strategies were
compared against a well-known civil engineering technique,
and conclusions drawn

Item Type: Book Section
ISBN: 978-3-211-83364-3
Electronic ISBN: 978-3-7091-6384-9
Additional Information: 4th International Conference on Artificial Neural Networks and Genetic Algorithms, ICANNGA '99, Portoroz, Slovenia
Uncontrolled Keywords: traffic signal timings; multi-junction road timings; optimisation; network delay; genetic algorithm;
University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Computing
Dewey Decimal Subjects: 000 Computer science, information & general works > 000 Computer science, knowledge & systems > 006 Special Computer Methods
Library of Congress Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Item ID: 3158
Depositing User: Computing Research
Date Deposited: 08 Sep 2010 15:02
Last Modified: 26 Mar 2014 10:49

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