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On Predicting the Taxi-Passenger Demand: A Real-Time Approach

Title
On Predicting the Taxi-Passenger Demand: A Real-Time Approach
Type
Article in International Conference Proceedings Book
Year
2013
Authors
Luís Moreira-Matias
(Author)
FEUP
Gama, João
(Author)
FEP
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Ferreira, Michel
(Author)
FCUP
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Mendes-Moreira, João
(Author)
FEUP
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Damas, Luís
(Author)
Other
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Conference proceedings International
Pages: 54-65
16th Portuguese Conference on Artificial Intelligence (EPIA)
Angra do Heroismo, PORTUGAL, SEP 09-12, 2013
Scientific classification
FOS: Natural sciences > Computer and information sciences
CORDIS: Physical sciences > Computer science > Cybernetics > Artificial intelligence
Other information
Authenticus ID: P-008-EFG
Abstract (EN): Informed driving is becoming a key feature to increase the sustainability of taxi companies. Some recent works are exploring the data broadcasted by each vehicle to provide live information for decision making. In this paper, we propose a method to employ a learning model based on historical GPS data in a real-time environment. Our goal is to predict the spatiotemporal distribution of the Taxi-Passenger demand in a short time horizon. We did so by using learning concepts originally proposed to a well-known online algorithm: the perceptron [1]. The results were promising: we accomplished a satisfactory performance to output the next prediction using a short amount of resources.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 12
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