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Computer Science > Machine Learning

arXiv:2109.09832 (cs)
[Submitted on 20 Sep 2021]

Title:Weak Signals in the Mobility Landscape: Car Sharing in Ten European Cities

Authors:Chiara Boldrini, Raffaele Bruno, Haitam Laarabi
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Abstract:Car sharing is one the pillars of a smart transportation infrastructure, as it is expected to reduce traffic congestion, parking demands and pollution in our cities. From the point of view of demand modelling, car sharing is a weak signal in the city landscape: only a small percentage of the population uses it, and thus it is difficult to study reliably with traditional techniques such as households travel diaries. In this work, we depart from these traditional approaches and we leverage web-based, digital records about vehicle availability in 10 European cities for one of the major active car sharing operators. We discuss which sociodemographic and urban activity indicators are associated with variations in car sharing demand, which forecasting approach (among the most popular in the related literature) is better suited to predict pickup and drop-off events, and how the spatio-temporal information about vehicle availability can be used to infer how different zones in a city are used by customers. We conclude the paper by presenting a direct application of the analysis of the dataset, aimed at identifying where to locate maintenance facilities within the car sharing operation area.
Comments: This work was partially funded by the ESPRIT, REPLICATE and SoBigData projects, which have received funding from the European Union's Horizon 2020 research and innovation programme under grant agreements No 653395, No 691735, and No 654024, respectively. arXiv admin note: text overlap with arXiv:1708.00497
Subjects: Machine Learning (cs.LG); Computers and Society (cs.CY)
Cite as: arXiv:2109.09832 [cs.LG]
  (or arXiv:2109.09832v1 [cs.LG] for this version)
  https://doi.org/10.48550/arXiv.2109.09832
Journal reference: EPJ Data Sci. 8, 7 (2019)
Related DOI: https://doi.org/10.1140/epjds/s13688-019-0186-8

Submission history

From: Chiara Boldrini [view email]
[v1] Mon, 20 Sep 2021 20:37:25 UTC (891 KB)
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