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Cluster Analysis on Sustainable Transportation: The Case of New York City Open Data
Cape Breton University, Sydney, Canada.
Halmstad University, School of Information Technology, Center for Applied Intelligent Systems Research (CAISR). Cape Breton University, Sydney, Canada.ORCID iD: 0000-0002-9557-0043
Halmstad University, School of Information Technology.ORCID iD: 0000-0002-7796-5201
2022 (English)In: 2022 International Conference on Applied Artificial Intelligence (ICAPAI), IEEE, 2022Conference paper, Published paper (Refereed)
Abstract [en]

Artificial Intelligence (AI) provides the opportunity to analyze complex transportation domains from various perspectives. Sustainability is one of the important transportation factors vital for a robust, fair, and efficient living environment and the livability of a city. This article leverages different feature engineering techniques on the New York City mobility dataset to identify the significant sustainability factors and employ the k-means clustering technique to cluster the commuters based on their transportation modes and demographics. Cluster analysis is performed based on the specified features and sustainable mode of transportation. Our cluster analysis of commuters on the New York City dataset shows that demographic information such as gender or race does not influence the sustainable mode of transportation, while the "start location"of travellers and their car access are influencing factors on sustainability. © 2022 IEEE.

Place, publisher, year, edition, pages
IEEE, 2022.
Keywords [en]
Clustering, Feature engineering, K-means, Sustainability, Transportation
National Category
Computer and Information Sciences
Research subject
Smart Cities and Communities
Identifiers
URN: urn:nbn:se:hh:diva-49332DOI: 10.1109/ICAPAI55158.2022.9801569ISI: 000852632300002Scopus ID: 2-s2.0-85134170663ISBN: 978-1-6654-6781-0 (electronic)ISBN: 978-1-6654-6782-7 (print)OAI: oai:DiVA.org:hh-49332DiVA, id: diva2:1725693
Conference
2022 International Conference on Applied Artificial Intelligence, ICAPAI 2022, 5 May, Halden, Norway, 2022
Available from: 2023-01-11 Created: 2023-01-11 Last updated: 2023-10-05Bibliographically approved

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Rajabi, EnayatNowaczyk, Sławomir

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf