Iterative Learning Control for Ramp Metering on Service Station On-ramps

Fuente: arXiv
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Auteurs principaux: Xiang, Hongxi, Cenedese, Carlo, Balta, Efe C., Lygeros, John
Format: Preprint
Publié: 2024
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author Xiang, Hongxi
Cenedese, Carlo
Balta, Efe C.
Lygeros, John
author_facet Xiang, Hongxi
Cenedese, Carlo
Balta, Efe C.
Lygeros, John
contents Congestion on highways has become a significant social problem due to the increasing number of vehicles, leading to considerable waste of time 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.
format Preprint
id arxiv_https___arxiv_org_abs_2411_11108
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Iterative Learning Control for Ramp Metering on Service Station On-ramps
Xiang, Hongxi
Cenedese, Carlo
Balta, Efe C.
Lygeros, John
Systems and Control
Congestion on highways has become a significant social problem due to the increasing number of vehicles, leading to considerable waste of time 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.
title Iterative Learning Control for Ramp Metering on Service Station On-ramps
topic Systems and Control
url https://arxiv.org/abs/2411.11108