Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/144625
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dc.contributor.authorWang, Dien_US
dc.contributor.authorWu, Evanen_US
dc.contributor.authorTan, Ah-Hweeen_US
dc.date.accessioned2020-11-16T05:15:20Z-
dc.date.available2020-11-16T05:15:20Z-
dc.date.issued2018-
dc.identifier.citationWang, D., Wu, E., & Tan, A.-H. (2018). Analysis of public transportation patterns in a densely populated city with station-based shared bikes. Proceedings of the 3rd International Conference on Crowd Science and Engineering, 1-8. doi:10.1145/3265689.3265697en_US
dc.identifier.isbn9781450365871-
dc.identifier.urihttps://hdl.handle.net/10356/144625-
dc.description.abstractDensely populated cities face great challenges of high transportation demand and limited physical space. Thus, in these cities, the public transportation system is heavily relied on. Conventional public transportation modes such as bus, taxi and subway have been globally deployed over the past century. In the last decade, a new type of public transportation mode, shared bike, emerged in many cities. These shared bikes are deployed by either government-regulated or profit-driven companies and are either station-based or station-less. Nonetheless, all of them are designed to better solve the last-mile problem in densely populated cities as complements to the conventional public transportation system. In this paper, we analyse the public transportation patterns in a densely populated city, Chicago, USA, using comprehensive datasets covering the transportation records on shared bikes, buses, taxis and subways collected over one year’s time. Specifically, we apply self-regulated clustering methods to reveal both the majority transportation patterns and the irregular ones. Other than reporting the autonomously discovered transportation patterns, we also show that our method achieves better clustering performance than the benchmarking methods.en_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.language.isoenen_US
dc.rights© 2018 Association for Computing Machinery. All rights reserved. This paper was published in Proceedings of the 3rd International Conference on Crowd Science and Engineering and is made available with permission of Association for Computing Machinery.en_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titleAnalysis of public transportation patterns in a densely populated city with station-based shared bikesen_US
dc.typeConference Paperen
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.contributor.conferenceThe 3rd International Conference on Crowd Science and Engineering (ICCSE’18)en_US
dc.contributor.organizationJoint NTU-UBC Research Centre of Excellence in Active Living for the Elderlyen_US
dc.identifier.doi10.1145/3265689.3265697-
dc.description.versionAccepted versionen_US
dc.identifier.scopus2-s2.0-85056724308-
dc.identifier.spage1en_US
dc.identifier.epage8en_US
dc.subject.keywordsSelf-regulated Clusteringen_US
dc.subject.keywordsShared Bikeen_US
dc.citation.conferencelocationSingaporeen_US
dc.description.acknowledgementThis research is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its IDM Futures Funding Initiative.en_US
item.grantfulltextopen-
item.fulltextWith Fulltext-
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