@article{ref1,
title="A non-additive path-based reward credit scheme for traffic congestion management",
journal="Transportation research part E: logistics and transportation review",
year="2023",
author="Luan, Mingye and Waller, S. Travis and Rey, David",
volume="179",
number="",
pages="e103291-e103291",
abstract="This study investigates the potential of non-additive path-based pricing for congestion management in urban transportation networks. We propose a novel path-based reward credit scheme to provide commuter incentives with the goal of reducing traffic congestion. We consider that a known proportion of commuters subscribe to this reward credit scheme and may earn credits when traveling in the network. We introduce a bilevel optimization formulation to determine optimal non-additive, path-based reward credits under traffic equilibrium conditions. In this formulation, the follower problem is a parameterized user equilibrium traffic assignment problem with two classes of users and non-additive path costs. We develop a single-level reformulation based on its first-order optimality conditions and derive theoretical properties of the reward credit scheme. Customized branch-and-bound algorithms are designed to solve the problem. We also introduce a heuristic approach that repeatedly solves parameterized follower problems to enhance scalability. We report numerical results that demonstrate the computational efficiency of the proposed methods over a benchmarking approach. We conduct a comprehensive evaluation of this path-based reward credit scheme compared with a link-based subsidy pricing scheme. We find that, on average, under a limited budget and a user participation level of at least 40%, the proposed path-based incentive mechanism yields larger reductions in traffic congestion over link-based approaches.<p /> <p>Language: en</p>",
language="en",
issn="1366-5545",
doi="10.1016/j.tre.2023.103291",
url="http://dx.doi.org/10.1016/j.tre.2023.103291"
}