Weak Signals in the Mobility Landscape: Car Sharing in Ten European Cities
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 4 of its 60 references that are in the map. First posted on arXiv 20 Sep 2021.
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References · 4
- 2013A significance test for the lassocited by 20
- 2013Geo-Spotting: Mining Online Location-based Services for Optimal Retail Store Placementcited by 9
- 2015Mining Open Datasets for Transparency in Taxi Transport in Metropolitan Environmentscited by 1
- 2017Car sharing through the data analysis lenscited by 1
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