Data fusion in intelligent transportation systems: Progress and challenges - A survey

Authors:
Nour-Eddin El Faouzi;Henry Leung;Ajeesh Kurian
Affiliations:
Transport and Traffic Engineering Laboratory, INRETS, LICIT, Bron F-69675, France and ENTPE, LICIT, Vaulx-en-Velin F-69518, France and University of Lyon, Lyon F-69003, France;Department of Electrical and Computer Engineering, University of Calgary, Calgary, Alberta, Canada T2N 1N4;Department of Electrical and Computer Engineering, University of Calgary, Calgary, Alberta, Canada T2N 1N4
Venue:
Information Fusion
Year:
2011

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Abstract

In intelligent transportation systems (ITS), transportation infrastructure is complimented with information and communication technologies with the objectives of attaining improved passenger safety, reduced transportation time and fuel consumption and vehicle wear and tear. With the advent of modern communication and computational devices and inexpensive sensors it is possible to collect and process data from a number of sources. Data fusion (DF) is collection of techniques by which information from multiple sources are combined in order to reach a better inference. DF is an inevitable tool for ITS. This paper provides a survey of how DF is used in different areas of ITS.