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Adaptive freeway ramp metering and variable speed limit control: a genetic-fuzzy approach

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3 Author(s)
Amir Hosein Ghods ; University of Waterloo, Ontario, Canada ; Ashkan Rahimi Kian ; Masoud Tabibi

This paper deals with the problem of ramp metering along with speed limit control of the freeway networks in order to reduce the peak hour congestion. An adaptive fuzzy control is proposed to solve the problem. To calibrate the fuzzy controller, 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 the simulation results. The proposed method is tested in a stretch of a freeway network. To evaluate the efficiency of the method, the test results are examined and compared with traditional ALINEA controller and genetic-fuzzy ramp metering only case. The paper concludes that the proposed adaptive genetic-fuzzy control is expected to enhance the performance of the freeway traffic network control while keeping the computational simplicity of the problem.

Published in:

IEEE Intelligent Transportation Systems Magazine  (Volume:1 ,  Issue: 1 )