Eco-friendly lane reservation-based autonomous truck transportation network design.
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| Title: | Eco-friendly lane reservation-based autonomous truck transportation network design. |
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| Authors: | Xu, Ling1,2 (AUTHOR), Wu, Peng1 (AUTHOR) wupeng88857@gmail.com, Chu, Chengbin2 (AUTHOR) chengbin.chu@univ-eiffel.fr, D'Ariano, Andrea3 (AUTHOR) |
| Source: | International Journal of Production Research. Dec2024, Vol. 62 Issue 23, p8239-8259. 21p. |
| Subjects: | Freight & freightage, Freight trucking, Carbon emissions, Transportation safety measures, Sensitivity analysis |
| Abstract: | As one of the primary sources of carbon emissions, transportation sector has proposed various measures to reduce its carbon emissions. Introducing energy-efficient and low-carbon autonomous trucks into freight transportation is highly promising, but faces various challenges, especially safety issues. This study addresses eco-friendly lane reservation-based autonomous truck transportation network design for transportation safety and low carbon emissions. It aims to optimally implement dedicated truck lanes in an existing network and design dedicated routes for autonomous truck transportation to simultaneously minimise the negative impact caused by dedicated truck lanes and carbon emissions of the entire transportation system. We first formulate this problem into a bi-objective integer linear program. Then, an ϵ-constraint-based two-stage algorithm (ETSA) is proposed to solve it based on explored problem properties. A case study based on the well-known Sioux Falls network is conducted to demonstrate the applicability of the proposed model and algorithm. Computational results for 310 instances from the literature demonstrate that the proposed algorithm significantly outperforms the ϵ-constraint combined with the proposed ILP in obtaining the Pareto front. Moreover, helpful managerial insights are derived based on sensitivity analysis. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 180732665 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Eco-friendly lane reservation-based autonomous truck transportation network design. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Xu%2C+Ling%22">Xu, Ling</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wu%2C+Peng%22">Wu, Peng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wupeng88857@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Chu%2C+Chengbin%22">Chu, Chengbin</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> chengbin.chu@univ-eiffel.fr</i><br /><searchLink fieldCode="AR" term="%22D'Ariano%2C+Andrea%22">D'Ariano, Andrea</searchLink><relatesTo>3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Dec2024, Vol. 62 Issue 23, p8239-8259. 21p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Freight+%26+freightage%22">Freight & freightage</searchLink><br /><searchLink fieldCode="DE" term="%22Freight+trucking%22">Freight trucking</searchLink><br /><searchLink fieldCode="DE" term="%22Carbon+emissions%22">Carbon emissions</searchLink><br /><searchLink fieldCode="DE" term="%22Transportation+safety+measures%22">Transportation safety measures</searchLink><br /><searchLink fieldCode="DE" term="%22Sensitivity+analysis%22">Sensitivity analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: As one of the primary sources of carbon emissions, transportation sector has proposed various measures to reduce its carbon emissions. Introducing energy-efficient and low-carbon autonomous trucks into freight transportation is highly promising, but faces various challenges, especially safety issues. This study addresses eco-friendly lane reservation-based autonomous truck transportation network design for transportation safety and low carbon emissions. It aims to optimally implement dedicated truck lanes in an existing network and design dedicated routes for autonomous truck transportation to simultaneously minimise the negative impact caused by dedicated truck lanes and carbon emissions of the entire transportation system. We first formulate this problem into a bi-objective integer linear program. Then, an ϵ-constraint-based two-stage algorithm (ETSA) is proposed to solve it based on explored problem properties. A case study based on the well-known Sioux Falls network is conducted to demonstrate the applicability of the proposed model and algorithm. Computational results for 310 instances from the literature demonstrate that the proposed algorithm significantly outperforms the ϵ-constraint combined with the proposed ILP in obtaining the Pareto front. Moreover, helpful managerial insights are derived based on sensitivity analysis. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/00207543.2024.2335329 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 8239 Subjects: – SubjectFull: Freight & freightage Type: general – SubjectFull: Freight trucking Type: general – SubjectFull: Carbon emissions Type: general – SubjectFull: Transportation safety measures Type: general – SubjectFull: Sensitivity analysis Type: general Titles: – TitleFull: Eco-friendly lane reservation-based autonomous truck transportation network design. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Xu, Ling – PersonEntity: Name: NameFull: Wu, Peng – PersonEntity: Name: NameFull: Chu, Chengbin – PersonEntity: Name: NameFull: D'Ariano, Andrea IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 00207543 Numbering: – Type: volume Value: 62 – Type: issue Value: 23 Titles: – TitleFull: International Journal of Production Research Type: main |
| ResultId | 1 |
