An iterative learning control(ILC) based phase splits strategy is proposed for oversaturated urban traffic network by exploiting the repetitive pattern of the traffic flows. First, an improved time-varying store and f...
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ISBN:
(纸本)9781509009107
An iterative learning control(ILC) based phase splits strategy is proposed for oversaturated urban traffic network by exploiting the repetitive pattern of the traffic flows. First, an improved time-varying store and forward model with unknown saturation flows, turning ratios, and traffic demands is proposed to describe the urban traffic dynamics. Then, by formulating the control problem as phase splits problem of all junctions in the network, ILC based phase splits strategy is designed to find controlinput signals(phase splits) such that output signals(actual traffic density of each link) in the network track the desired one. The ILC based phase splits strategy with controlinput constraints is further designed and analyzed to highlight the applicability of phase splits methods.
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