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Albuquerque, V., Andrade, F., Ferreira, J. C. & Dias, M. S. (2020). Understanding spatiotemporal station and trip activity patterns in the Lisbon bike-sharing system. In Intelligent transport systems, from research and development to the market uptake. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. (pp. 16-34).: Springer.

V. Albuquerque et al.,  "Understanding spatiotemporal station and trip activity patterns in the Lisbon bike-sharing system", in Intelligent transport systems, from research and development to the market uptake. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Springer, 2020, vol. 364, pp. 16-34

@inproceedings{albuquerque2020_1714633353644,
	author = "Albuquerque, V. and Andrade, F. and Ferreira, J. C. and Dias, M. S.",
	title = "Understanding spatiotemporal station and trip activity patterns in the Lisbon bike-sharing system",
	booktitle = "Intelligent transport systems, from research and development to the market uptake. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering",
	year = "2020",
	editor = "",
	volume = "364",
	number = "",
	series = "",
	doi = "10.1007/978-3-030-71454-3_2",
	pages = "16-34",
	publisher = "Springer",
	address = "",
	organization = "",
	url = "https://link.springer.com/book/10.1007/978-3-030-71454-3"
}

TY  - CPAPER
TI  - Understanding spatiotemporal station and trip activity patterns in the Lisbon bike-sharing system
T2  - Intelligent transport systems, from research and development to the market uptake. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
VL  - 364
AU  - Albuquerque, V.
AU  - Andrade, F.
AU  - Ferreira, J. C.
AU  - Dias, M. S.
PY  - 2020
SP  - 16-34
SN  - 1867-8211
DO  - 10.1007/978-3-030-71454-3_2
UR  - https://link.springer.com/book/10.1007/978-3-030-71454-3
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.
ER  -