Road Traffic Measurement and Related Data Fusion Methodology for Traffic Estimation

Road Traffic Measurement and Related Data Fusion Methodology for Traffic Estimation

The knowledge of road traffic parameters is of crucial importance to ensure state-of-the-art traffic services either in public or private transport. In our days, a plethora of road traffic data are continuously collected producing historical and real-time traffic information as well. The available i...

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Main Authors: Tettamanti Tamás, Horváth Márton Tamás, Varga István
Format: Article
Language:English
Published: Sciendo 2014-12-01
Series:Transport and Telecommunication
Subjects:
road traffic estimation
data fusion
switching kalman filter
Online Access:https://doi.org/10.2478/ttj-2014-0023
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spelling doaj-e8c8f24a5e5d4f9dac6b92d08726cd6e2021-09-05T21:24:15ZengSciendoTransport and Telecommunication1407-61792014-12-0115426927910.2478/ttj-2014-0023ttj-2014-0023Road Traffic Measurement and Related Data Fusion Methodology for Traffic EstimationTettamanti Tamás0Horváth Márton Tamás1Varga István2Department of Control for Transportation and Vehicle Systems, Budapest University of Technology and Economics, Stoczek J. u. 2., H-1111 Budapest, HungaryDepartment of Control for Transportation and Vehicle Systems, Budapest University of Technology and Economics, Stoczek J. u. 2., H-1111 Budapest, HungaryDepartment of Control for Transportation and Vehicle Systems, Budapest University of Technology and Economics, Stoczek J. u. 2., H-1111 Budapest, HungaryThe knowledge of road traffic parameters is of crucial importance to ensure state-of-the-art traffic services either in public or private transport. In our days, a plethora of road traffic data are continuously collected producing historical and real-time traffic information as well. The available information, however, arrive from inhomogeneous sensor systems. Therefore, a data fusion methodology is proposed based on Switching Kalman Filter. The concept enables efficient travel time estimation for urban road traffic network. On the other hand, the method may contribute to a better macroscopic traffic modelling.https://doi.org/10.2478/ttj-2014-0023road traffic estimationdata fusionswitching kalman filter
collection DOAJ
language English
format Article
sources DOAJ
author Tettamanti Tamás
Horváth Márton Tamás
Varga István
spellingShingle Tettamanti Tamás
Horváth Márton Tamás
Varga István
Road Traffic Measurement and Related Data Fusion Methodology for Traffic Estimation
Transport and Telecommunication
road traffic estimation
data fusion
switching kalman filter
author_facet Tettamanti Tamás
Horváth Márton Tamás
Varga István
author_sort Tettamanti Tamás
title Road Traffic Measurement and Related Data Fusion Methodology for Traffic Estimation
title_short Road Traffic Measurement and Related Data Fusion Methodology for Traffic Estimation
title_full Road Traffic Measurement and Related Data Fusion Methodology for Traffic Estimation
title_fullStr Road Traffic Measurement and Related Data Fusion Methodology for Traffic Estimation
title_full_unstemmed Road Traffic Measurement and Related Data Fusion Methodology for Traffic Estimation
title_sort road traffic measurement and related data fusion methodology for traffic estimation
publisher Sciendo
series Transport and Telecommunication
issn 1407-6179
publishDate 2014-12-01
description The knowledge of road traffic parameters is of crucial importance to ensure state-of-the-art traffic services either in public or private transport. In our days, a plethora of road traffic data are continuously collected producing historical and real-time traffic information as well. The available information, however, arrive from inhomogeneous sensor systems. Therefore, a data fusion methodology is proposed based on Switching Kalman Filter. The concept enables efficient travel time estimation for urban road traffic network. On the other hand, the method may contribute to a better macroscopic traffic modelling.
topic road traffic estimation
data fusion
switching kalman filter
url https://doi.org/10.2478/ttj-2014-0023
work_keys_str_mv AT tettamantitamas roadtrafficmeasurementandrelateddatafusionmethodologyfortrafficestimation
AT horvathmartontamas roadtrafficmeasurementandrelateddatafusionmethodologyfortrafficestimation
AT vargaistvan roadtrafficmeasurementandrelateddatafusionmethodologyfortrafficestimation
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