Iterative Learning Control for Ramp Metering on Service Station On-ramps
Hongxi Xiang (ETH Zürich)
Carlo Cenedese (ETH Zürich, TU Delft - Mechanical Engineering)
Efe C. Balta (Inspire AG, ETH Zürich)
John Lygeros (ETH Zürich)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Highway congestion leads to significant delays and pollution. Regulating the outflow from the Service Station can help alleviate this congestion. Notably, traffic flows follow recurring patterns over days and weeks, allowing for the application of Iterative Learning Control (ILC). Building on these insights, we propose an ILC approach based on the Cell Transmission Model with service stations (CTM-s). It is shown that ILC can effectively compensate for potential inaccuracies in model parameter estimates by leveraging historical data.