A Cluster-Based Approach Using Smartphone Data for Bike-Sharing Docking Stations Identification: Lisbon Case Study

Tiago Fontes,Paulo Novais,Miguel Arantes,Paulo V Figueiredo

doi:10.3390/smartcities5010016

Abstract

Urban mobility is a massive issue in the current century, being widely promoted the need of adopting sustainable solutions regarding transportation within large urban centres. The evolution of technologies has democratised smart cities to better plan and manage their mobility solutions, without compromising the social, economic, and environmental impacts. Pursuing the carbon neutrality and the climate agreement goals, soft mobility is one of the most popular emerging methods to provide greener alternatives regarding mobility. Among these transportation modes are the bicycle, which has been widely used in several public systems across the world, one of them being in Lisbon. This article provides a decision support system for bike-sharing docking stations for three council parishes of the city, namely, Parque das Nações, Marvila, and Beato. Taking advantage of clustering methods and GSM data from a telecommunication operator, this study pretends to highlight a novel approach to identify soft mobility hotspots, in specific bike-sharing docking stations, for suited mobility management systems in Lisbon’s city centre.

Highlights

In the last decades, increasing population growth has created several concerns, especially in urban centres, as it brings new environmental, economic, and social challenges, as shown by environmental issues surrounding human overpopulation [1]
The K-Means Clustering Algorithm was applied to the provided GSM data, with the 14 clusters as output expected
We looked for the existing nearby services and other Points of Interest (PoI) that might justify that identification, apart from one of major factors in mobility: bicycle lanes closeness

Summary

Introduction

In the last decades, increasing population growth has created several concerns, especially in urban centres, as it brings new environmental, economic, and social challenges, as shown by environmental issues surrounding human overpopulation [1]. Climate change and environmental degradation represent a European and a global concern. The seventeen Sustainable Development Goals (SDGs) are at its heart, an urgent call to action from all countries (both developed and in development). They recognise, among several topics, stimulating economic growth while tackling climate change. The thirteenth goal is “Making cities and human settlements inclusive, safe, resilient and sustainable,” clarifying the global need to promote sustainability in one of the most fundamental ways, mobility

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Results

Conclusion