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Distributionally robust Markovian traffic equilibrium

Distributionally robust Markovian traffic equilibrium
Distributionally robust Markovian traffic equilibrium
In a Markovian traffic equilibrium model, users move toward their destinations by a sequence of successive link choices using a discrete choice model at each node, taking congestion into account. Although a convex optimization formulation is available to compute the equilibrium flows for a continuous distribution of link utilities, practical applications have thus far been mainly restricted to the multinomial logit model and its variants. In this paper, we relax the assumption of a complete joint distribution of link utilities to only knowledge on the marginal distributions and propose a new convex optimization formulation for a distributionally robust Markovian traffic equilibrium. The formulation is provably efficiently solvable and has the flexibility of allowing for general marginal distributions, thus capturing different types of nonidentical, skewed, and heavy-tailed distributions at the link level.
0041-1655
1546-1562
Ahipasaoglu, Selin
d69f1b80-5c05-4d50-82df-c13b87b02687
Arikan, Ugur
a067331d-3875-4755-bb18-acab5e7db6bb
Natarajan, Karthik
f06e68cf-288e-4280-8cdb-5b5d7d397ce0
Ahipasaoglu, Selin
d69f1b80-5c05-4d50-82df-c13b87b02687
Arikan, Ugur
a067331d-3875-4755-bb18-acab5e7db6bb
Natarajan, Karthik
f06e68cf-288e-4280-8cdb-5b5d7d397ce0

Ahipasaoglu, Selin, Arikan, Ugur and Natarajan, Karthik (2019) Distributionally robust Markovian traffic equilibrium. Transportation Science, 53 (6), 1546-1562. (doi:10.1287/trsc.2019.0910).

Record type: Article

Abstract

In a Markovian traffic equilibrium model, users move toward their destinations by a sequence of successive link choices using a discrete choice model at each node, taking congestion into account. Although a convex optimization formulation is available to compute the equilibrium flows for a continuous distribution of link utilities, practical applications have thus far been mainly restricted to the multinomial logit model and its variants. In this paper, we relax the assumption of a complete joint distribution of link utilities to only knowledge on the marginal distributions and propose a new convex optimization formulation for a distributionally robust Markovian traffic equilibrium. The formulation is provably efficiently solvable and has the flexibility of allowing for general marginal distributions, thus capturing different types of nonidentical, skewed, and heavy-tailed distributions at the link level.

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More information

e-pub ahead of print date: 31 October 2019
Published date: November 2019

Identifiers

Local EPrints ID: 443183
URI: http://eprints.soton.ac.uk/id/eprint/443183
ISSN: 0041-1655
PURE UUID: efbff7eb-ccdf-4936-a24f-962e989fb197
ORCID for Selin Ahipasaoglu: ORCID iD orcid.org/0000-0003-1371-315X

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Date deposited: 13 Aug 2020 16:38
Last modified: 17 Mar 2024 04:03

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Contributors

Author: Ugur Arikan
Author: Karthik Natarajan

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