A Hybrid Fuzzy Genetic Algorithm for an Adaptive Traffic Signal System
This paper presents a hybrid algorithm that combines Fuzzy Logic Controller (FLC) and Genetic Algorithms (GAs) and its application on a traffic signal system. FLCs have been widely used in many applications in diverse areas, such as control system, pattern recognition, signal processing, and forecas...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2015/378156 |
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| _version_ | 1832546550917627904 |
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| author | S. M. Odeh A. M. Mora M. N. Moreno J. J. Merelo |
| author_facet | S. M. Odeh A. M. Mora M. N. Moreno J. J. Merelo |
| author_sort | S. M. Odeh |
| collection | DOAJ |
| description | This paper presents a hybrid algorithm that combines Fuzzy Logic Controller (FLC) and Genetic Algorithms (GAs) and its application on a traffic signal system. FLCs have been widely used in many applications in diverse areas, such as control system, pattern recognition, signal processing, and forecasting. They are, essentially, rule-based systems, in which the definition of these rules and fuzzy membership functions is generally based on verbally formulated rules that overlap through the parameter space. They have a great influence over the performance of the system. On the other hand, the Genetic Algorithm is a metaheuristic that provides a robust search in complex spaces. In this work, it has been used to adapt the decision rules of FLCs that define an intelligent traffic signal system, obtaining a higher performance than a classical FLC-based control. The simulation results yielded by the hybrid algorithm show an improvement of up to 34% in the performance with respect to a standard traffic signal controller, Conventional Traffic Signal Controller (CTC), and up to 31% in the comparison with a traditional logic controller, FLC. |
| format | Article |
| id | doaj-art-a418d92e6b5646f78f8867c9f038681f |
| institution | Kabale University |
| issn | 1687-7101 1687-711X |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-a418d92e6b5646f78f8867c9f038681f2025-02-03T06:48:29ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2015-01-01201510.1155/2015/378156378156A Hybrid Fuzzy Genetic Algorithm for an Adaptive Traffic Signal SystemS. M. Odeh0A. M. Mora1M. N. Moreno2J. J. Merelo3Department of Computer and Information System, Bethlehem University, Bethlehem, State of PalestineDepartment of Computer Architecture and Technology, University of Granada, Granada, SpainDepartment of Computing, Faculty of Sciences, University of Salamanca, Salamanca, SpainDepartment of Computer Architecture and Technology, University of Granada, Granada, SpainThis paper presents a hybrid algorithm that combines Fuzzy Logic Controller (FLC) and Genetic Algorithms (GAs) and its application on a traffic signal system. FLCs have been widely used in many applications in diverse areas, such as control system, pattern recognition, signal processing, and forecasting. They are, essentially, rule-based systems, in which the definition of these rules and fuzzy membership functions is generally based on verbally formulated rules that overlap through the parameter space. They have a great influence over the performance of the system. On the other hand, the Genetic Algorithm is a metaheuristic that provides a robust search in complex spaces. In this work, it has been used to adapt the decision rules of FLCs that define an intelligent traffic signal system, obtaining a higher performance than a classical FLC-based control. The simulation results yielded by the hybrid algorithm show an improvement of up to 34% in the performance with respect to a standard traffic signal controller, Conventional Traffic Signal Controller (CTC), and up to 31% in the comparison with a traditional logic controller, FLC.http://dx.doi.org/10.1155/2015/378156 |
| spellingShingle | S. M. Odeh A. M. Mora M. N. Moreno J. J. Merelo A Hybrid Fuzzy Genetic Algorithm for an Adaptive Traffic Signal System Advances in Fuzzy Systems |
| title | A Hybrid Fuzzy Genetic Algorithm for an Adaptive Traffic Signal System |
| title_full | A Hybrid Fuzzy Genetic Algorithm for an Adaptive Traffic Signal System |
| title_fullStr | A Hybrid Fuzzy Genetic Algorithm for an Adaptive Traffic Signal System |
| title_full_unstemmed | A Hybrid Fuzzy Genetic Algorithm for an Adaptive Traffic Signal System |
| title_short | A Hybrid Fuzzy Genetic Algorithm for an Adaptive Traffic Signal System |
| title_sort | hybrid fuzzy genetic algorithm for an adaptive traffic signal system |
| url | http://dx.doi.org/10.1155/2015/378156 |
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