Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/5362
Title: On Predicting the Taxi-Passenger Demand: A Real-Time Approach
Authors: Luís Moreira Matias
João Gama
Michel Ferreira
João Mendes Moreira
Damas,L
Issue Date: 2013
Abstract: 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.
URI: http://repositorio.inesctec.pt/handle/123456789/5362
http://dx.doi.org/10.1007/978-3-642-40669-0_6
metadata.dc.type: conferenceObject
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Appears in Collections:CRACS - Other Publications
LIAAD - Other Publications

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