A Predictive Model for the Passenger Demand on a Taxi Network

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2012

Autores

Luís Matias (Autor) FEUP; João Gama (Autor) FEP; Michel Ferreira (Autor) FCUP; Luís Damas (Autor) Outra

Ata de Conferência Internacional

Título: 2012 15TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC)

Páginas: 1014-1019

15th International IEEE Conference on Intelligent Transportation Systems (ITSC)

Anchorage, AK, SEP 16-19, 2012

Indexação

ISI Web of Knowledge - 47 Citações

Scopus - 65 Citações

Classificação Científica

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

Outras Informações

ID Authenticus: P-002-EHV

DOI: 10.1109/ITSC.2012.6338680

Abstract (EN): In the last decade, the real-time vehicle location systems attracted everyone attention for the new kind of rich spatio-temporal information. The fast processing of this large amount of information is a growing and explosive challenge. Taxi companies are already exploring such information in efficient taxi dispatching and time-saving route finding. In this paper, we propose a novel methodology to produce online short term predictions on the passenger demand spatial distribution over 63 taxi stands in the city of Porto, Portugal. We did so using time series forecasting techniques to the processed events constantly communicated for 441 taxi vehicles. Our tests - using 4 months of real data - demonstrated that this model is a true major contribution to the driver mobility intelligence: 76% of the 86411 demanded taxi services were accurately forecasted in a 30 minutes time horizon.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6