On improving operational planning and control in Public Transportation Networks using streaming Data: A Machine Learning Approach

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2014

Autores

Luís Moreira Matias (Autor) FEUP; João Mendes Moreira (Autor) FEUP; João Gama (Autor) FEP; Michel Ferreira (Autor) FCUP

Ata de Conferência Internacional

Título: ECML/PKDD 2014 PhD Session

Páginas: 41-50

ECML/PKDD 2014 PhD Session

Nancy, France, 15 a 19 de Setembro de 2014

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

CORDIS: Ciências Físicas > Ciência de computadores > Cibernética > Inteligência artificial

Outras Informações

Abstract (EN): Nowadays, transportation vehicles are equipped with intelligent sensors. Together, they form collaborative networks that broadcast real-time data about mobility patterns in urban areas. Online intelligent transportation systems for taxi dispatching, time-saving route finding or automatic vehicle location are already exploring such information in the taxi/buses transport industries. In this PhD spotlight paper, the authors present two ML applications focused on improving the operation of Public Transportation (PT) systems: 1) Bus Bunching (BB) Online Detection and 2) Taxi-Passenger Demand Prediction. By doing so, we intend to give a brief overview of the type of approaches applicable to these type of problems. Our frameworks are straightforward. By employing online learning frameworks we are able to use both historical and real-time data to update the inference models. The results are promising.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11