Online predictive model for taxi services

• Type: Article in International Conference Proceedings Book
• Date: 2012

Authors

Luis Moreira-Matias (Author) Other; João Gama (Author) FEP; Michel Ferreira (Author) FCUP; João Mendes-Moreira (Author) FEUP; Luís Damas (Author) Other

Conference proceedings International

Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Pages: 230-240

11th International Symposium on Intelligent Data Analysis, IDA 2012

Helsinki, 25 October 2012 through 27 October 2012

Indexing

ISI Web of Science

Scopus - 10 Citations

Scientific classification

CORDIS: Physical sciences > Computer science

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-008-70R

DOI: 10.1007/978-3-642-34156-4_22

Abstract (EN): In recent years, both companies and researchers have been exploring intelligent data analysis to increase the profitability of the taxi industry. Intelligent systems for online taxi dispatching and time saving route finding have been built to do so. In this paper, we propose a novel methodology to produce online predictions regarding the spatial distribution of passenger demand throughout taxi stand networks. We have done so by assembling two well-known time series short-term forecast models: the time-varying Poisson models and ARIMA models. Our tests were performed using data gathered over a period of 6 months and collected from 63 taxi stands within the city of Porto, Portugal. Our results demonstrate that this model is a true major contribution to the driver mobility intelligence: 78% of the 253745 demanded taxi services were correctly forecasted in a 30 minutes horizon. © Springer-Verlag Berlin Heidelberg 2012.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11