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Article: Demand Analysis and Distribution of Single-Trip Ticket Cards for Urban Rail Transit

TitleDemand Analysis and Distribution of Single-Trip Ticket Cards for Urban Rail Transit
Authors
KeywordsDecision making process
Distribution models
Distribution volume
Effective management
Loading and unloading
Issue Date2020
PublisherHindawi Publishing Corporation. The Journal's web site is located at http://www.hindawi.com/journals/mpe/index.html
Citation
Mathematical Problems in Engineering: theory, methods and applications, 2020, v. 2020, p. article no. 5605479 How to Cite?
AbstractIn the current urban rail transit systems, nearly 15% of passengers are noncommuter travelers who use single-trip ticket cards (ticket cards). Accordingly, the effective management of ticket cards is of great importance. This article suggests a time series model for use in predicting ticket card storage based on the characteristics of ticket cards collected by an automatic fare collection (AFC) system. The distribution cycle, station types, and distribution volume of each station are also determined. Then, drawing on small package transportation feasibility theory, an unbalanced distribution model between production and demand (unbalanced distribution model), as well as a hybrid distribution model of loading and unloading (hybrid distribution model), is established. Application of these models to the Beijing Subway system is used to verify the efficiency and feasibility of such a hybrid distribution model. The analysis and results offer insights into usage patterns of urban rail transit ticket cards, providing solid evidence for a relative decision-making process.
Persistent Identifierhttp://hdl.handle.net/10722/289956
ISSN
2019 Impact Factor: 1.009
2015 SCImago Journal Rankings: 0.285

 

DC FieldValueLanguage
dc.contributor.authorWang, ZJ-
dc.contributor.authorLi, JQ-
dc.contributor.authorWU, JY-
dc.contributor.authorYang, ZG-
dc.date.accessioned2020-10-22T08:19:52Z-
dc.date.available2020-10-22T08:19:52Z-
dc.date.issued2020-
dc.identifier.citationMathematical Problems in Engineering: theory, methods and applications, 2020, v. 2020, p. article no. 5605479-
dc.identifier.issn1024-123X-
dc.identifier.urihttp://hdl.handle.net/10722/289956-
dc.description.abstractIn the current urban rail transit systems, nearly 15% of passengers are noncommuter travelers who use single-trip ticket cards (ticket cards). Accordingly, the effective management of ticket cards is of great importance. This article suggests a time series model for use in predicting ticket card storage based on the characteristics of ticket cards collected by an automatic fare collection (AFC) system. The distribution cycle, station types, and distribution volume of each station are also determined. Then, drawing on small package transportation feasibility theory, an unbalanced distribution model between production and demand (unbalanced distribution model), as well as a hybrid distribution model of loading and unloading (hybrid distribution model), is established. Application of these models to the Beijing Subway system is used to verify the efficiency and feasibility of such a hybrid distribution model. The analysis and results offer insights into usage patterns of urban rail transit ticket cards, providing solid evidence for a relative decision-making process.-
dc.languageeng-
dc.publisherHindawi Publishing Corporation. The Journal's web site is located at http://www.hindawi.com/journals/mpe/index.html-
dc.relation.ispartofMathematical Problems in Engineering: theory, methods and applications-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectDecision making process-
dc.subjectDistribution models-
dc.subjectDistribution volume-
dc.subjectEffective management-
dc.subjectLoading and unloading-
dc.titleDemand Analysis and Distribution of Single-Trip Ticket Cards for Urban Rail Transit-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1155/2020/5605479-
dc.identifier.scopuseid_2-s2.0-85089137002-
dc.identifier.hkuros317133-
dc.identifier.volume2020-
dc.identifier.spagearticle no. 5605479-
dc.identifier.epagearticle no. 5605479-
dc.publisher.placeUnited States-

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