Tesi, 2019, ENG

Mining human mobility data and social media for smart ride sharing

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.

Keywords

Ride-sharing, Ride Matching Algorithms, Activity-Based, Social Media, Attendance Prediction

CNR authors

Monteiro De Lira Vinicius Cezar

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

ID: 425440

Year: 2019

Type: Tesi

Creation: 2020-07-14 10:29:40.000

Last update: 2020-07-15 16:18:24.000

External links

OAI-PMH: Dublin Core

OAI-PMH: Mods

OAI-PMH: RDF

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:425440