Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/7631
Title: Artificial bee colony-based algorithm for optimising traffic signal timings
Authors: Dell’Orco, M.
Başkan, Ö.
Marinelli, M.
Keywords: Algorithms
Genetic algorithms
Optimization
Social networking (online)
Soft computing
Timing circuits
Traffic control
World Wide Web
Artificial bee colonies
Artificial bee colony algorithms (ABC)
Foraging behaviors
Meta-heuristic approach
Optimal setting
Performance indices
Signal timing optimization
Traffic signal timings
Traffic signals
Publisher: Springer Verlag
Abstract: This study proposed Artificial Bee Colony (ABC) algorithm for finding optimal setting of traffic signals in coordinated signalized networks for given fixed set of link flows. For optimizing traffic signal timings in coordinated signalized networks, ABC with TRANSYT-7F (ABCTRANS) model is developed. The ABC algorithm is a new population-based metaheuristic approach, and it is inspired by the foraging behavior of honeybee swarm. TRANSYT-7F traffic model is used to estimate total network performance index (PI). The ABCTRANS is tested on medium sized signalized road network. Results showed that the proposed model is slightly better in signal timing optimization in terms of final values of PI when it is compared with TRANSYT-7F in which Genetic Algorithm (GA) and Hillclimbing (HC) methods are exist. Results also showed that the ABCTRANS model improves the medium sized network’s PI by 2.4 and 2.7% when it is compared with GA and HC methods. © Springer International Publishing Switzerland 2014.
URI: https://hdl.handle.net/11499/7631
https://doi.org/10.1007/978-3-319-00930-8_29
ISBN: 21945357 (ISSN)
9783319009292
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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