Genetic algorithm based signal optimizer for oversaturated urban signalized intersection

Tan, Min Keng and Chuo, Helen Sin Ee and Chin, Renee Ka Yin and Kiam, Beng Yeo and Teo, Kenneth Tze Kin (2017) Genetic algorithm based signal optimizer for oversaturated urban signalized intersection.

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Official URL: https://ieeexplore.ieee.org/document/7804762

Abstract

Relieving traffic congestion is an urgent call for traffic engineering. Although various adaptive control strategies have been reported in literature to reduce the travel delay, most of them are not tested under oversaturated condition, where the traffic demand is higher than the road capacity. Therefore, this work proposes genetic algorithm (GA) to optimize the traffic signals for reducing the average delay at the at-grade crossed intersection under oversaturated condition. A comprehensive traffic model has been dexeloped as the testbed. The average delay experienced by every vehicle to traverse the intersection is taken as performance metric to evaluate the performances of the formulated GA. The simulation results show the formulated GA is able to optimize the traffic signals and minimize the average delay of the intersection to 55.2 sec or equivalent to level-of-service (LOS) D.

Item Type:	Proceedings
Keyword:	Genetic algorithm , Traffic signal optimization , Oversaturated traffic condition
Subjects:	H Social Sciences > HE Transportation and Communications > HE1-9990 Transportation and communications > HE331-380 Traffic engineering. Roads and highways. Streets Q Science > QA Mathematics > QA1-939 Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software
Department:	FACULTY > Faculty of Engineering
Depositing User:	DG MASNIAH AHMAD -
Date Deposited:	24 Feb 2022 16:50
Last Modified:	24 Feb 2022 16:50
URI:	https://eprints.ums.edu.my/id/eprint/31757

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