Please use this identifier to cite or link to this item: http://hdl.handle.net/10216/83023
Author(s): Luís Moreira-Matias
João Mendes-Moreira
João Gama
Michel Ferreira
Title: On Improving Operational Planning and Control in Public Transportation Networks using Streaming Data: A Machine Learning Approach
Issue Date: 2014
Abstract: 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.
Subject: Inteligência artificial, Engenharia electrotécnica, electrónica e informática
Call Number: 92678
URI: http://hdl.handle.net/10216/83023
Source: ECML/PKDD 2014 PhD Session
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FCUP - Artigo em Livro de Atas de Conferência Internacional
FEUP - Artigo em Livro de Atas de Conferência Internacional
FEP - Artigo em Livro de Atas de Conferência Internacional

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