Multiple Objective Genetic Algorithms for Solving Traffic Signal Optimization Issue at a Complex Intersection: A Case Study in Taichung City, Taiwan
Do Van Manh1, 2, *, Liang- Tay Lin1, Pei Liu1, Dinh Tuan Hai3
1 College of Construction and Development, Feng Chia University, Taichung, Taiwan 40724, R.O.C.
2 Civil Engineering Faculty University of Transport and communications, Hanoi, Vietnam
3 Faculty of Urban Management, Hanoi Architectural University, Hanoi, Vietnam
In optimal traffic signal timing, some researchers proposed a single objective genetic algorithm to optimize the timing plan at an isolated intersection. However, the genetic algorithm belongs to a natural selection procession. It means that a suggested model might have a local, optimal result instead of global optimization. A few researchers have tried to avoid local optimization values by making many assumptions for the suggested model, these estimations lacked comprehensive theoretical bases in the transportation field.
The objective of this study is to contribute a comprehensive optimization solution, by applying multiple objective genetic algorithms, to minimize the effective green time and cycle length at a complex urban intersection.
First, the fitness function was established by the minimum issues of average control delay and queue length at the complex isolated intersection. Secondly, constraint functions were identified based on a scientific basis to provide a comprehensive hypothetical model. After running the hypothetical model with single and multiple objective genetic algorithms and real traffic flow data, the results were compared between the use of multiple genetic algorithms and the use of a single-objective genetic algorithm, between an existing traffic signal timing plan and a suggested traffic signal timing plan. Then, the traffic simulation model for the complex intersection was generated to validate the effectiveness of the suggested method.
After comparison, the suggested model was found to be more efficient than the existing traffic signal timing at the complex intersection.
This study demonstrated multiple objective genetic algorithms that overwhelmed the single objective genetic algorithm in optimal traffic signal timing. The multiple objective genetic algorithms could be effectively used to handle traffic optimization at a complex large-scale intersection. Furthermore, a comprehensive solution of applying multiple genetic algorithms to deal with traffic signal optimization has been generated in this research.
Keywords: Optimal traffic signal timing, Traffic control, Intelligent transport system, Single-multiple objective genetic algorithms, Simulation, Urban areas.
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
* Address correspondence to this author at College of Construction and Development, Feng Chia University, Taichung, Taiwan 40724, R.O.C; Tel: +886-4-24517250; E-mails: Manhdv@utc.edu.vn