Pricing vehicle emissions and congestion externalities using a dynamic traffic network simulator

Vosough, Shaghayegh; Palma, André de; Lindsey, Robin

doi:10.1016/j.tra.2022.04.017

Cited by 8 publications

(1 citation statement)

References 76 publications

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“…In recent times, there has been a growing recognition among trained professionals and specialists of the need to focus on multimodal transportation in light of its various sustainable benefits [8][9][10][11]. The European Union (EU) has also recognized the negative externalities associated with road haulage, such as delays, congestion, and environmental impact from CO 2 emissions [12][13][14][15][16]. To address these issues, the EU has set ambitious targets for a competitive and resource-efficient transport system, including a shift towards more sustainable modes of transport like rail and waterway transport [17].…”

Section: Introductionmentioning

confidence: 99%

Min-cost route problems for multimodal sustainable logistics cooperation

Cerrone,

Sciomachen,

Truvolo

2023

Preprint

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This paper addresses the urgent need for sustainable logistics practices in the context of the current global climate emergency. In particular, the proposed study faces the problem of defining the paths of different carriers to transport goods while reducing the environmental impact in a multimodal logistics network. We present a mathematical programming framework designed to answer questions related to the use of available payload, the number of transhipments needed, and the transport cost, including environmental impact. In practice, we solve multimodal shortest path problems in which paths of different carriers to transport units of goods from an origin to a destination intersect each other. The search for the optimal solution considers several parameters oriented towards the paradigm of cooperative logistics and the green impact. In fact, the proposed framework is able to gather information on a series of transports carried out by vehicles of different types (trucks, trains, ships, airplanes). Up to 3.240 test instances were generated and solved to optimality using the proposed mathematical model based on the underlying multimodal graph.

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