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 16:02
    Last Modified: 26 Mar 2014 10:49

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