Bianca Iacomussi
Spatio-temporal algorithms for predicting the usage of bike-sharing systems.
Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2021
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Abstract
With the recent concerns about climate change and the tendency to promote smart mobility systems, there is an increasing interest on shared means of transport around the world, such as Bike Sharing Systems (BSS), which constitute a valid green alternative for movements within cities. Given these circumstances, many studies have been carried out by the scientific community to improve the service of Bike Sharing Systems focusing on customer satisfaction, by finding optimal locations for bike stations, studying mobility patterns in the cities of interest, enhancing bike redistribution among stations, offering customers predictions in the next minutes about bike availability in the stations.
This thesis aims at contributing at the last two questions by proposing predictive models to forecast in the short term the number of bikes available and free slots in each station of the Barcelona BSS, for example in 20 minutes or an hour
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