Modelling time-varying mobility flows using function-on-function regression: analysis of a bike sharing system in the city of Milan.

Keywords

Statistical learning
Sustainable mobility
Code:
19/2019
Title:
Modelling time-varying mobility flows using function-on-function regression: analysis of a bike sharing system in the city of Milan.
Date:
Monday 17th June 2019
Author(s):
Torti, A.; Pini, A.; Vantini, S.
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Abstract:
In today’s world bike sharing systems are becoming increasingly common in all main cities around the world. To understand the spatio-temporal patterns of how people move by bike through the city of Milan, we apply functional data analysis to study the flows of a bike sharing mobility network. We introduce a complete pipeline to properly analyse and model functional data through a concurrent functional-on-functional model taking into account the effects of weather conditions and calendar on the bike flows.