Abstract

This paper introduces an optimization problem (P) and a solution strategy to design variable-speed-limit controls for a highway that is subject to traffic congestion and uncertain vehicle arrival and departure. By employing a finite data-set of samples of the uncertain variables, we aim to find a data-driven solution that has a guaranteed out-of-sample performance. In principle, such formulation leads to an intractable problem (P) as the distribution of the uncertainty variable is unknown. By adopting a distributionally robust optimization approach, this work presents a tractable reformulation of (P) and an efficient algorithm that provides a suboptimal solution that retains the out-of-sample performance guarantee. A simulation illustrates the effectiveness of this method.

Comment: 10 pages, 2 figures, submitted to ECC 2019


Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.23919/ecc.2019.8796026
https://dblp.uni-trier.de/db/conf/eucc/eucc2019.html#LiFM19,
https://arxiv.org/pdf/1810.11385.pdf,
http://export.arxiv.org/abs/1810.11385,
http://export.arxiv.org/pdf/1810.11385,
https://aps.arxiv.org/abs/1810.11385,
https://tw.arxiv.org/abs/1810.11385,
https://ru.arxiv.org/abs/1810.11385,
https://ru.arxiv.org/pdf/1810.11385,
https://aps.arxiv.org/pdf/1810.11385,
https://il.arxiv.org/abs/1810.11385,
https://academic.microsoft.com/#/detail/2898314220
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Published on 01/01/2018

Volume 2018, 2018
DOI: 10.23919/ecc.2019.8796026
Licence: CC BY-NC-SA license

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