Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.trc.2007.06.007
Title: An iterative learning approach for density control of freeway traffic flow via ramp metering
Authors: Hou, Z.
Xu, J.-X. 
Yan, J.
Keywords: Freeway traffic control
Iterative learning control
Macroscopic traffic flow
Ramp metering
Traffic density control
Issue Date: Feb-2008
Citation: Hou, Z., Xu, J.-X., Yan, J. (2008-02). An iterative learning approach for density control of freeway traffic flow via ramp metering. Transportation Research Part C: Emerging Technologies 16 (1) : 71-97. ScholarBank@NUS Repository. https://doi.org/10.1016/j.trc.2007.06.007
Abstract: In this work, we apply the iterative learning control approach to address the traffic density control problem in a macroscopic level freeway environment with ramp metering. The traffic density control problem is first formulated into an output tracking and disturbance rejection problem. Through rigorous analysis, it is shown that the iterative learning control method can effectively deal with this class of control problem and greatly improve the traffic response. Next, the iterative learning control is combined with error feedback in a complementary modular manner to achieve the output tracking and system robustness. The effectiveness of the new approach is further verified through case studies with intensive simulations. © 2007 Elsevier Ltd. All rights reserved.
Source Title: Transportation Research Part C: Emerging Technologies
URI: http://scholarbank.nus.edu.sg/handle/10635/55044
ISSN: 0968090X
DOI: 10.1016/j.trc.2007.06.007
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