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Title:
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SAMPLING CAR-SHARING DATA TO EVALUATE URBAN TRAFFIC BEHAVIOUR |
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Author(s):
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Andrea Trentini and Federico Losacco |
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ISBN:
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978-989-8533-69-2 |
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Editors:
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Pedro Isaías and Hans Weghorn |
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Year:
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2017 |
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Edition:
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Single |
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Keywords:
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Urban Congestion, Traffic Monitoring, Open Data, Public Accountancy, Anti-Pollution Policies |
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Type:
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Short Paper |
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First Page:
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295 |
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Last Page:
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299 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Nowadays, in modern countries, urban traffic per se must be addressed as a problem. The congestion factor is fought by introducing regulations to reduce private traffic: tolls, dedicated lanes, narrow lanes, low speed limits, reduced parking availability, etc. Some help can come from car-sharing, i.e., pools of shared vehicles to be rented for short periods of time. Car-sharing vendors publish (not entirely/easily accessible) data about the state of their vehicle pool... Can this data be used to analyse the overall traffic behaviour in town? The authors scraped car-sharing vendors websites for a couple of years, made data uniform and then queried and graphed the dataset. Some interesting findings are: the lung effect (morning moving-in, evening moving-out); evening peak usage (people using car-sharing instead of taxicabs to go out at night for leisure); vehicle usage (the total number of busy vehicles at any time) never goes beyond 70%. Moreover, by combining information about parking locations, movement vectors can be drawn to evaluate frequent paths. |
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