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

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 shared modes, bike-sharing systems. This paper poses a research question introduces corresponding systematic literature review, focusing machine learning techniques’ contributions applied systems improve mobility. The preferred reporting items for reviews meta-analyses (PRISMA) method was adopted identify specific factors that influence systems, resulting in an analysis 35 papers published between 2015 2019, creating outline future research. By means review bibliometric analysis, algorithms were identified two groups: classification prediction.