Monteiro de Lira V.
CNR-ISTI, Pisa, Italy and UFPE, Brazil and Università di Pisa, Pisa, Italy
People living in highly-populated cities increasingly suffer an impoverishment of their quality of life due to pollution and traffic congestion problems caused by the huge number of circulating vehicles. Indeed, the reduction the number of circulating vehicles is one of the most difficult challenges in large metropolitan areas. This PhD thesis proposes a research contribution with the final objective of reducing travelling vehicles. This is done towards two different directions: on the one hand, we aim to improve the efficacy of ride sharing systems, creating a larger number of ride possibilities based on the passengers destination activities; on the other hand, we propose a social media analysis method, based on machine learning, to identify transportation demand to an event.
Ride-sharing, Ride Matching Algorithms, Activity-Based, Social Media, Attendance Prediction
Monteiro De Lira Vinicius Cezar
ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"
CNR authors
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:425440