Adaptive Freeway Ramp Metering and Variable Speed Limit Control: A Genetic-Fuzzy Approach

This paper deals with the problem of ramp metering along with speed limit control of freeway networks in order to reduce peak hour congestion. An adaptive fuzzy control is proposed to solve the problem. To calibrate the fuzzy controller, a genetic algorithm is used to tune the fuzzy sets parameters so that the total time spent in the network remains minimum. A macroscopic traffic model is used for tuning the controller in an adaptive scheme and for presenting simulation results. The proposed method is tested in a stretch of a freeway network. To evaluate the efficiency of the method, test results are examined and compared with traditional ALINEA controller and genetic-fuzzy ramp metering only case. It is concluded that the proposed adaptive genetic-fuzzy control is wil enhance performance of the freeway traffic network control while maintaining its computational simplicity.

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  • Supplemental Notes:
    • Abstract reprinted with permission of IEEE.
  • Authors:
    • Ghods, Amir Hosein
    • Kian, Ashkan Rahimi
    • Tabibi, Masoud
  • Publication Date: 2009


  • English

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  • Accession Number: 01141897
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Oct 16 2009 2:27PM