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Evolutionary algorithms for traffic signal optimisation: A survey
Evolutionary algorithms for traffic signal optimisation: A survey
Published: 2009
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Buchtitel: Proceedings of mobil.TUM 2009 - International Scientific Conference on Mobility and Transport
Verlag: TU München
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Kurzfassung
Evolutionary algorithms are optimisation heuristics that are inspired by biological evolution.
They are relatively easy to comprehend and can be applied to any problem where a fitness
function for rating candidate solutions is available. Therefore, evolutionary algorithms have
been successfully applied to a wide range of real-world problems since their development in
the 1960s. Since several years, their application domain also includes the optimisation of
traffic signal systems. Here, the challenges are the often time-consuming and noisy fitness
evaluations that are in many cases based on stochastic traffic simulations. The resulting time
requirements make the use of evolutionary algorithms a challenging task especially in on-line
scenarios where the traffic signal system has to be continuously adapted to changing traffic
demands.
This paper presents a structured overview of evolutionary algorithm applications in traffic
signal optimisation. Different (off- and on-line) scenarios are presented and techniques for
reducing their time requirements are discussed. Furthermore, multi-objective evolutionary
algorithms that simultaneously treat several (contradicting) objectives are introduced.