Dynamic Ride-Matching for Large-Scale Transportation Systems

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dc.authoridde Souza, Felipe/0000-0002-4858-141X
dc.authoridAuld, Joshua/0000-0002-2492-0093
dc.authoridCokyasar, Taner/0000-0001-9687-6725
dc.contributor.authorCokyasar, Taner
dc.contributor.authorde Souza, Felipe
dc.contributor.authorAuld, Joshua
dc.contributor.authorVerbas, Omer
dc.date.accessioned2025-03-17T12:25:33Z
dc.date.available2025-03-17T12:25:33Z
dc.date.issued2022
dc.departmentTarsus Üniversitesi
dc.description.abstractEfficient dynamic ride-matching (DRM) in large-scale transportation systems is a key driver in transport simulations to yield answers to challenging problems. Although the DRM problem is simple to solve, it quickly becomes a computationally challenging problem in large-scale transportation system simulations. Therefore, this study thoroughly examines the DRM problem dynamics and proposes an optimization-based solution framework to solve the problem efficiently. To benefit from parallel computing and reduce computational times, the problem's network is divided into clusters utilizing a commonly used unsupervised machine learning algorithm along with a linear programming model. Then, these sub-problems are solved using another linear program to finalize the ride-matching. At the clustering level, the framework allows users adjusting cluster sizes to balance the trade-off between the computational time savings and the solution quality deviation. A case study in the Chicago Metropolitan Area, U.S., illustrates that the framework can reduce the average computational time by 58% at the cost of increasing the average pick up time by 26% compared with a system optimum, that is, non-clustered, approach. Another case study in a relatively small city, Bloomington, Illinois, U.S., shows that the framework provides quite similar results to the system-optimum approach in approximately 62% less computational time.
dc.description.sponsorshipU.S. Department of Energy, Vehicle Technologies Office, under the Systems and Modeling for Accelerated Research in Transportation Mobility Laboratory Consortium, an initiative of the Energy Efficient Mobility Systems Program
dc.description.sponsorshipThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This material is based on work supported by the U.S. Department of Energy, Vehicle Technologies Office, under the Systems and Modeling for Accelerated Research in Transportation Mobility Laboratory Consortium, an initiative of the Energy Efficient Mobility Systems Program.
dc.identifier.doi10.1177/03611981211049422
dc.identifier.endpage182
dc.identifier.issn0361-1981
dc.identifier.issn2169-4052
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85128174900
dc.identifier.scopusqualityQ2
dc.identifier.startpage172
dc.identifier.urihttps://doi.org/10.1177/03611981211049422
dc.identifier.urihttps://hdl.handle.net/20.500.13099/1737
dc.identifier.volume2676
dc.identifier.wosWOS:000712152000001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSage Publications Inc
dc.relation.ispartofTransportation Research Record
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250316
dc.subjectpublic transportation
dc.subjectinnovative public transportation services and technologies
dc.subjectmobility as a service (MaaS)
dc.subjectrural
dc.subjectintercity bus
dc.subjectspecialized transportation
dc.titleDynamic Ride-Matching for Large-Scale Transportation Systems
dc.typeArticle

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