Please use this identifier to cite or link to this item: https://doi.org/10.1109/TVT.2007.891431
Title: Freeway traffic control using iterative learning control-based ramp metering and speed signaling
Authors: Hou, Z.
Xu, J.-X. 
Zhong, H.
Keywords: Freeway ramp metering
Iterative learning control (ILC)
Macroscopic traffic flow model
Speed control
Traffic density control
Issue Date: Mar-2007
Source: Hou, Z.,Xu, J.-X.,Zhong, H. (2007-03). Freeway traffic control using iterative learning control-based ramp metering and speed signaling. IEEE Transactions on Vehicular Technology 56 (2) : 466-477. ScholarBank@NUS Repository. https://doi.org/10.1109/TVT.2007.891431
Abstract: In this paper, an iterative learning approach for the freeway density control under ramp metering and speed regulation is developed in a macroscopic level traffic environment. Rigorous analyses show that the proposed learning control schemes guarantee the asymptotic convergence of the traffic density to the desired one. The two major features of the learning-based density control are 1) less prior modeling knowledge required in the control system design and 2) the ability to reject exogenous traffic perturbations. The control schemes are applied to a freeway model, and simulation results confirm the efficacy of the proposed approach. © 2007 IEEE.
Source Title: IEEE Transactions on Vehicular Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/56089
ISSN: 00189545
DOI: 10.1109/TVT.2007.891431
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