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Authors: Ali Hajbabaie and Rahim F. Benekohal

Affiliation: University of Illinois at Urbana Champaign, United States

Keyword(s): Traffic Signal Optimization, Oversaturated Network, Evolution Strategies, Genetic Algorithms.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Evolutionary Graphics ; Genetic Algorithms ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Soft Computing

Abstract: This paper compares the performance of Evolution Strategies (ES) with simple Genetic Algorithms (GAs) in finding optimal or near optimal signal timing in a small network of oversaturated intersections with turning movements. The challenge is to find the green times and the offsets in all intersections so that total vehicle-mile of the network is maximized. By incorporating ES or GA with the micro-simulation package, CORSIM, we have been able to find the near optimal signal timing for the above-mentioned network. The results of this study showed that both algorithms were able to find the near optimal signal timing in the network. For all populations tested in this study, GA yielded higher fitness values than ES. GA with a population size of 300, and selection pressure of 10% produced the highest fitness values. In GA for medium and large size populations, a lower selection pressure produced better results while for small size population a large selection pressure resulted in better fi tness values. In ES for small size population, larger µ/λ yielded better results, for medium size population both µ/λ ratios produced similar results, and for large size population smaller µ/λ provided better results. (More)

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Paper citation in several formats:
Hajbabaie, A. and Benekohal, R. (2009). EVOLUTION STRATEGIES COMPARED TO GENETIC ALGORITHMS IN FINDING OPTIMAL SIGNAL TIMING FOR OVERSATURATED TRANSPORTATION NETWORK. In Proceedings of the International Joint Conference on Computational Intelligence (IJCCI 2009) - ICEC; ISBN 978-989-674-014-6; ISSN 2184-3236, SciTePress, pages 296-301. DOI: 10.5220/0002316202960301

@conference{icec09,
author={Ali Hajbabaie. and Rahim F. Benekohal.},
title={EVOLUTION STRATEGIES COMPARED TO GENETIC ALGORITHMS IN FINDING OPTIMAL SIGNAL TIMING FOR OVERSATURATED TRANSPORTATION NETWORK},
booktitle={Proceedings of the International Joint Conference on Computational Intelligence (IJCCI 2009) - ICEC},
year={2009},
pages={296-301},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002316202960301},
isbn={978-989-674-014-6},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the International Joint Conference on Computational Intelligence (IJCCI 2009) - ICEC
TI - EVOLUTION STRATEGIES COMPARED TO GENETIC ALGORITHMS IN FINDING OPTIMAL SIGNAL TIMING FOR OVERSATURATED TRANSPORTATION NETWORK
SN - 978-989-674-014-6
IS - 2184-3236
AU - Hajbabaie, A.
AU - Benekohal, R.
PY - 2009
SP - 296
EP - 301
DO - 10.5220/0002316202960301
PB - SciTePress