Distributionally Robust Markovian Traffic Equilibrium

Selin Damla Ahipaşaoğlu (), Uğur Arıkan () and Karthik Natarajan ()
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Selin Damla Ahipaşaoğlu: Engineering Systems and Design, Singapore University of Technology and Design, Singapore 487372
Uğur Arıkan: Engineering Systems and Design, Singapore University of Technology and Design, Singapore 487372
Karthik Natarajan: Engineering Systems and Design, Singapore University of Technology and Design, Singapore 487372

Transportation Science, 2019, vol. 53, issue 6, 1546-1562

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.

Keywords: Markovian traffic equilibrium; distributionally robust; convex optimization (search for similar items in EconPapers)
Date: 2019
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