Mining Taxi Data for Describing City in the Context of Mobility, Sociality, and Environment: Lessons Learned

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2016

Autores

Veloso, M (Autor) Outra; Phithakkitnukoon, S (Autor) Outra; Bento, C (Autor) Outra; Pedro M. d'Orey (Autor) FEUP

Ata de Conferência Internacional

Título: IEEE 19th International Conference on Intelligent Transportation Systems: Proceedings

Páginas: 217-222

ITSC 2016 - 19th IEEE International Conference on Intelligent Transportation Systems

Rio de Janeiro, 1 de novembro de 2016

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00M-CQB

DOI: 10.1109/itsc.2016.7795557

Abstract (EN): Taxi is an important way of transportation. With the equipped location sensors, it becomes a probe sensing urban dynamics. In this work, we review and improve three approaches that use taxi data to explore the city dynamics of Lisbon, Portugal. We develop a naive Bayesian classifier to estimate taxi demand; analyze the correlation between taxi volume and mobile phone activity; and compare ANN and linear regression models to estimate NO2 concentrations, using taxi activity information and meteorological conditions.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6