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International Journal of Automotive Technology 2002;3(3): 89-94. |
| ADAPTIVE, REAL-TIME TRAFFIC CONTROL MANAGEMENT |
| G. NAKAMITI1, R. FREITAS2 |
1Rua Alaro Faria de Barros
2Paulista State University |
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| ABSTRACT |
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This paper presents an architecture for distributed control systems and its underlying methodological framework. Ideas and concepts of distributed systems, artificial intelligence, and soft computing are merged into a unique architecture to provide cooperation, flexibility, and adaptablility required by knowledge processing in intelligent control systems. The distinguished features of the architecture include a local problem solving capability to handle the specific requirements of each part of the system, an evolutionary case-based mechanism to improve performance and optimize controls, the use of linguistic variables as means for information aggregation, and fuzzy set theory to provide local control. A distributed traffic control system application is discussed to provide the details of the architecture, and to emphasize its usefulness. The performance of the distributed control system is compared with conventional control approaches under a variety of traffic situations. |
| Key Words:
Urban traffic control, Intelligent control, Computational intelligence |
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