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Title: Machine learning approaches to bike-sharing systems: A systematic literature review
Authors: Albuquerque, V.
Dias, J.
Bacao, F.
Keywords: Bike-sharing systems
Machine learning
PRISMA method
Issue Date: 2021
Publisher: MDPI
Abstract: Cities are moving towards new mobility strategies to tackle smart cities’ challenges such as carbon emission reduction, urban transport multimodality and mitigation of pandemic hazards, emphasising on the implementation of shared modes, such as bike-sharing systems. This paper poses a research question and introduces a corresponding systematic literature review, focusing on machine learning techniques’ contributions applied to bike-sharing systems to improve cities’ mobility. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) method was adopted to identify specific factors that influence bike-sharing systems, resulting in an analysis of 35 papers published between 2015 and 2019, creating an outline for future research. By means of systematic literature review and bibliometric analysis, machine learning algorithms were identified in two groups: classification and prediction.
Peer reviewed: yes
DOI: 10.3390/ijgi10020062
ISSN: 2220-9964
Appears in Collections:ISTAR-RI - Artigos em revistas científicas internacionais com arbitragem científica

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