International Journal of Automotive Technology

The Korean Society of Automotive Engineers (한국자동차공학회)
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ADAPTIVE, REAL-TIME TRAFFIC CONTROL MANAGEMENT

  • Published : 2002.09.01
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Abstract

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 adaptability 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.

Keywords

References

  1. Favilla, J., Machion, A. and Gomide, F. (1993). Fuzzy Traffic control: Adaptative strategies, Second IEEE Intemational Conference on Fuzzy Systems, San Prancisco, CA, 506-511
  2. Goldberg, D. (1989). Genetic Atgorithms in Search,Optimization, and Machine Leaming, Addison-WesleyPubl. Co.
  3. Hoyer, R. and Jumar, U. (1994). Fuzzy control of trafficlights, Third IEEE IntemationaI Conference on Fuzzy Systems, Orlando, FL, 1526-1531
  4. Kelsey, R., Bisset, K. and Jamshidi, M. (1993). Asimulation environment for fuzzy control of trafficsystems, XII IFAC-Wortd Congress, Sydney, Australia, 553-556
  5. Nakamiti, G., Goncalves, R. and Gomide, F. (2000).Knowldge processing in control systems, in KnowIedge Engineering: Systems, Techniques and AppIications, Leondes, C. (Ed.), 2, Chapter 16, AcademicPress
  6. Nakamiti, G. and Gomide, F. (1994). An evolutive fuzzymechanism based on past expehences, SecondEuropean Congress on InteUigent Techniques and SoftComputing -EUFIT94, Aachen, Germany, 1211-1217
  7. Nakatsuyama, M., Nagahashi, H. and Nishizura, N.(1984). Fuzzy logic controller for a traffic junction inthe one-way arterial road, IX IFAC - World Congress, Budapest, Hungary, 13-18
  8. Papis, C. and Mamdani, E. (1977). A fuzzy logic controller for a traffic junction, IEEE Trans. Syst., Man, and Cybern., 7, 707-717 https://doi.org/10.1109/TSMC.1977.4309605
  9. Skowronski, W. and Shaw, L. (1993). Self-leaming fuzzy traffic controller for a traffic junction, I. European Congress on Intettigent Techniques and Soft Computing - EUFIT93, Aachen, Germany, 751-761
  10. Wohl, M. and Martin, B. (1967). Trafftc System Anatysis for Engineers and Planners, McGraw-Hill Book Co.