Journal
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
Volume 8, Issue 1, Pages 183-191Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/87.817703
Keywords
fuzzy pattern recognition; neural network; optimization; real time systems; traffic control
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Contraflow operation is frequently used for reducing traffic congestion near tunnels and bridges where traffic demands from the opposite directions vary periodically. In this work, a generic real-time optimal contraflow control method has been introduced. The introduced method integrates two important functional components: 1) an intelligent system with artificial neural network and fuzzy pattern recognition to accurately estimate the current traffic demands and predict the coming traffic demands, and 2) a mixed-variable, multilevel, constrained optimization to identify the optimal control parameters, Application of the developed method to a case study-dynamic contraflow traffic operation at the George Massey Tunnel in Vancouver, BC, Canada has significantly reduced traffic delay and congestion.
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