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Understanding Spatiotemporal Station and Trip Activity Patterns in the Lisbon Bike-Sharing System
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Orientador(es)
Resumo(s)
The development of the Internet of Things and mobile technology is connecting people and cities and generating large volumes of geolocated and space-time data. This paper identifies patterns in the Lisbon GIRA bike-sharing system (BSS), by analyzing the spatiotemporal distribution of travel distance, speed and duration, and correlating with environmental factors, such as weather conditions. Through cluster analysis the paper finds novel insights in origin-destination BSS stations, regarding spatial patterns and usage frequency. Such findings can inform decision makers and BSS operators towards service optimization, aiming at improving the Lisbon GIRA network planning in the framework of multimodal urban mobility.
Descrição
Albuquerque, V., Andrade, F., Ferreira, J. C., & Dias, M. S. (2021). Understanding Spatiotemporal Station and Trip Activity Patterns in the Lisbon Bike-Sharing System. In A. L. Martins, J. C. Ferreira, A. Kocian, & V. Costa (Eds.), Intelligent Transport Systems, From Research and Development to the Market Uptake: 4th EAI International Conference, INTSYS 2020, Proceedings (pp. 16-34). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 364 LNICST). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-71454-3_2
Palavras-chave
Bike-sharing system Cluster analysis K-means Mobility patterns Statistical analysis Urban mobility Computer Networks and Communications SDG 11 - Sustainable Cities and Communities
Contexto Educativo
Citação
Editora
Springer Science and Business Media Deutschland GmbH