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Article: Quantifying traffic emission reductions and traffic congestion alleviation from high-capacity ride-sharing

TitleQuantifying traffic emission reductions and traffic congestion alleviation from high-capacity ride-sharing
Authors
Keywordshigh-capacity ride-sharing
On-demand mobility
shared mobility
traffic congestion
traffic emissions
Issue Date5-Nov-2024
PublisherTaylor and Francis Group
Citation
Transportmetrica B: Transport Dynamics, 2024, v. 12, n. 1 How to Cite?
AbstractDespite the promising benefits that ride-sharing offers, there has been a lack of research on the benefits of high-capacity ride-sharing services. Prior research has also overlooked the relationship between traffic volume and the degree of traffic congestion and emissions. To address these gaps, this study develops an open-source agent-based simulation platform and a heuristic algorithm to quantify the benefits of high-capacity ride-sharing with significantly lower computational costs. The simulation platform integrates a traffic emission model and a speed-density traffic flow model to characterise the interactions between traffic congestion levels and emissions. The experiment results demonstrate that ride-sharing with vehicle capacities of 2, 4, and 6 passengers can alleviate total traffic congestion by approximately 3%, 4%, and 5%, and reduce traffic emissions of a ride-sourcing system by approximately 30%, 45%, and 50%, respectively. This study can guide transportation network companies in designing and managing more efficient and environment-friendly mobility systems.
Persistent Identifierhttp://hdl.handle.net/10722/353788
ISSN
2023 Impact Factor: 3.3
2023 SCImago Journal Rankings: 1.188
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChen, Wang-
dc.contributor.authorKe, Jintao-
dc.contributor.authorChen, Xiqun-
dc.date.accessioned2025-01-24T00:35:51Z-
dc.date.available2025-01-24T00:35:51Z-
dc.date.issued2024-11-05-
dc.identifier.citationTransportmetrica B: Transport Dynamics, 2024, v. 12, n. 1-
dc.identifier.issn2168-0566-
dc.identifier.urihttp://hdl.handle.net/10722/353788-
dc.description.abstractDespite the promising benefits that ride-sharing offers, there has been a lack of research on the benefits of high-capacity ride-sharing services. Prior research has also overlooked the relationship between traffic volume and the degree of traffic congestion and emissions. To address these gaps, this study develops an open-source agent-based simulation platform and a heuristic algorithm to quantify the benefits of high-capacity ride-sharing with significantly lower computational costs. The simulation platform integrates a traffic emission model and a speed-density traffic flow model to characterise the interactions between traffic congestion levels and emissions. The experiment results demonstrate that ride-sharing with vehicle capacities of 2, 4, and 6 passengers can alleviate total traffic congestion by approximately 3%, 4%, and 5%, and reduce traffic emissions of a ride-sourcing system by approximately 30%, 45%, and 50%, respectively. This study can guide transportation network companies in designing and managing more efficient and environment-friendly mobility systems.-
dc.languageeng-
dc.publisherTaylor and Francis Group-
dc.relation.ispartofTransportmetrica B: Transport Dynamics-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjecthigh-capacity ride-sharing-
dc.subjectOn-demand mobility-
dc.subjectshared mobility-
dc.subjecttraffic congestion-
dc.subjecttraffic emissions-
dc.titleQuantifying traffic emission reductions and traffic congestion alleviation from high-capacity ride-sharing-
dc.typeArticle-
dc.identifier.doi10.1080/21680566.2024.2423235-
dc.identifier.scopuseid_2-s2.0-85209583848-
dc.identifier.volume12-
dc.identifier.issue1-
dc.identifier.eissn2168-0582-
dc.identifier.isiWOS:001349154900001-
dc.identifier.issnl2168-0566-

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