Data-driven variable speed limit design for highways via distributionally robust optimization

Dan Li, Dariush Fooladivanda and Sonia Martínez
Proceedings of the 18th European Control Conference, Naples, Italy August 2019

Abstract:

This paper introduces an optimization problem and a solution strategy to design variable-speed-limit controls for a highway that is subject to traffic congestion and uncertain vehicle arrivals and departures. By employing a finite data-set of samples of the uncertain variables, we find a data-driven solution that has a guaranteed out-of-sample performance. In principle, such formulation leads to an intractable problem as the distribution of the uncertainty variable is unknown. By adopting a distributionally robust optimization approach, this work presents a tractable reformulation and an efficient algorithm that provides a suboptimal solution retaining the out-of-sample performance guarantee. Finally, we demonstrate the effectiveness of our algorithm numerically.

File: main.pdf

Bib-tex entry:

@InProceedings{DL-DF-SM:19-ecc,
author = {D. Li and D. Fooladivanda and S. Mart{\'\i}nez},
title = {Data-driven variable speed limit design for highways via distributionally robust optimization},
booktitle = {18th European Control Conference},
pages = {Data-driven variable speed limit design for highways via distributionally robust optimization},
year = {2019},
address = {Naples, Italy},
month = {June}
}