Machine Learning Approaches to Bike-Sharing Systems: A Systematic Literature Review

ISPRS International Journal of Geo-Information

Fernando Bacao¹  Vitória Albuquerque¹  Miguel Sales Dias¹ 

[1] NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312 Lisboa, Portugal;

关键词: bike-sharing systems;    machine learning;    classification;    prediction;    PRISMA method;   

DOI  :  10.3390/ijgi10020062

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown