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An intelligent contraflow control method for real-time optimal traffic scheduling using artificial neural network, fuzzy pattern recognition, and optimization

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2 Author(s)
Xue, D. ; Dept. of Mech. & Manuf. Eng., Calgary Univ., Alta., Canada ; Dong, Z.

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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Control Systems Technology, IEEE Transactions on  (Volume:8 ,  Issue: 1 )