TY - GEN
T1 - Understanding Spatiotemporal Station and Trip Activity Patterns in the Lisbon Bike-Sharing System
AU - Albuquerque, Vitória
AU - Andrade, Francisco
AU - Ferreira, João Carlos
AU - Dias, Miguel Sales
N1 - 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
PY - 2021/3/11
Y1 - 2021/3/11
N2 - 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.
AB - 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.
KW - Bike-sharing system
KW - Cluster analysis
KW - K-means
KW - Mobility patterns
KW - Statistical analysis
KW - Urban mobility
UR - http://www.scopus.com/inward/record.url?scp=85104459145&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-71454-3_2
DO - 10.1007/978-3-030-71454-3_2
M3 - Conference contribution
AN - SCOPUS:85104459145
SN - 9783030714536
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 16
EP - 34
BT - Intelligent Transport Systems, From Research and Development to the Market Uptake
A2 - Martins, Ana Lúcia
A2 - Ferreira, João C.
A2 - Kocian, Alexander
A2 - Costa, Vera
PB - Springer Science and Business Media Deutschland GmbH
T2 - 4th EAI International Conference on Intelligent Transport Systems, INTSYS 2020
Y2 - 3 December 2020 through 3 December 2020
ER -
