Hub-based truck platooning: Potentials and profitability

Larsen, Rune; Rich, Jeppe; Rasmussen, Thomas Kjær

doi:10.1016/j.tre.2019.05.005

Cited by 64 publications

(25 citation statements)

References 22 publications

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“…The estimated profit is about 4-5% of the fuel or about 38 eper trip for long-distance trucks. In a competitive market this profit can be a key issue [22].…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the first case, one of Fig. 1 Platooning hub [22] the platoons will check at the moment of departure to determine if there is any existing platoon with the same destination that you want to join. The connection is possible if the maximum number of vehicles and the maximum waiting time are not exceeded.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In this article we would like to further increase the benefits of platooning in a Physical Internet based logistics network. According to the concept outlined in [22], the platoons in the examined system travel only between hub centres. To take advantage of the connection we aim to create a model in which platoons can reconfigure themselves.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Similarly to the article written by [22], any restrictions that may result from technological sources and legislation will be removed. In addition, our simulation does not handle taxes and tolls.…”

Section: Limitations and Inputsmentioning

confidence: 99%

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Optimization of a physical internet based supply chain using reinforcement learning

Puskás

Budai

Bohács

2020

Eur. Transp. Res. Rev.

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Physical Internet based supply chains create open, global logistics systems that enable new types of collaboration among participants. The open system allows the logistical examination of vehicle technology innovations such as the platooning concept. This article explores the multiple platoon collaboration. For the reconfiguration of two platoons a heuristic and a reinforcement learning (RL) based models have been developed. To our knowledge, this work is the first attempt to apply an RL-based decision model to solve the problem of controlling platoon cooperation. Vehicle exchange between platoons is provided by a virtual hub. Depending on the various input parameters, the efficiency of the model was examined through numerical examples in terms of the target function based on the transportation cost. Models using platoon reconfiguration are also compared to the cases where no vehicle exchange is implemented. We have found that a reinforcement learning based model provides a more efficient solution for high incoming vehicle numbers and low dispatch interval, although for low vehicle numbers heuristics model performs better.

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“…The estimated profit is about 4-5% of the fuel or about 38 eper trip for long-distance trucks. In a competitive market this profit can be a key issue [22].…”

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Limitations and Inputsmentioning

confidence: 99%

See 2 more Smart Citations

Optimization of a physical internet based supply chain using reinforcement learning

Puskás

Budai

Bohács

2020

Eur. Transp. Res. Rev.

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show abstract

“…A number of papers focus on platoon planning in which trucks travel on a fixed path, thus ignoring any possible routing flexibility. These papers typically focus on a single highway lane or designated hub (Adler et al 2016, Larsen et al 2019. A number of these specifically focus on adjusting speeds to form platoons (Liang et al 2013, Sun andYin 2019).…”

Section: Related Literaturementioning

confidence: 99%