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.
Freeway traffic control using iterative learning control-based ramp metering and speed signaling
2007
12 Seiten, 29 Quellen
Article (Journal)
English
An iterative learning approach for density control of freeway traffic flow via ramp metering
Online Contents | 2008
|Freeway Traffic Flow Control with Anticipative Ramp Metering
British Library Conference Proceedings | 2005
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