The granular computing implementation for road traffic video-detector sampling rate finding

The method discussed in this contribution allows to estimate the necessary data granularity for an on-line traffic controlling, using the information recorded by digital video-camera. Due to define the data sampling rate modelling and analysis methods were applied. They are used for extracting predi...

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Main Author: Bartłomiej PŁACZEK
Format: Article
Language:English
Published: Silesian University of Technology 2009-01-01
Series:Transport Problems
Subjects:
Online Access:http://www.transportproblems.polsl.pl/pl/Archiwum/2009/zeszyt1/2009t4z1_07.pdf
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spelling doaj-d176aed2aa394d398d1e3c931f6a1fe02020-11-24T23:53:37ZengSilesian University of TechnologyTransport Problems1896-05962009-01-01415562The granular computing implementation for road traffic video-detector sampling rate findingBartłomiej PŁACZEKThe method discussed in this contribution allows to estimate the necessary data granularity for an on-line traffic controlling, using the information recorded by digital video-camera. Due to define the data sampling rate modelling and analysis methods were applied. They are used for extracting prediction rules of the traffic descriptors. The discussed scheme combines granular computing algorithms with assumptions of a cellular automata traffic model. It enables direct determination of temporal characteristics for the recognised and extracted traffic states. The traffic parameters prediction algorithm was introduced that allow determining the sampling time intervals of the video detection system.http://www.transportproblems.polsl.pl/pl/Archiwum/2009/zeszyt1/2009t4z1_07.pdfdigital video-cameragranular computing algorithmscellular automata traffic model
collection DOAJ
language English
format Article
sources DOAJ
author Bartłomiej PŁACZEK
spellingShingle Bartłomiej PŁACZEK
The granular computing implementation for road traffic video-detector sampling rate finding
Transport Problems
digital video-camera
granular computing algorithms
cellular automata traffic model
author_facet Bartłomiej PŁACZEK
author_sort Bartłomiej PŁACZEK
title The granular computing implementation for road traffic video-detector sampling rate finding
title_short The granular computing implementation for road traffic video-detector sampling rate finding
title_full The granular computing implementation for road traffic video-detector sampling rate finding
title_fullStr The granular computing implementation for road traffic video-detector sampling rate finding
title_full_unstemmed The granular computing implementation for road traffic video-detector sampling rate finding
title_sort granular computing implementation for road traffic video-detector sampling rate finding
publisher Silesian University of Technology
series Transport Problems
issn 1896-0596
publishDate 2009-01-01
description The method discussed in this contribution allows to estimate the necessary data granularity for an on-line traffic controlling, using the information recorded by digital video-camera. Due to define the data sampling rate modelling and analysis methods were applied. They are used for extracting prediction rules of the traffic descriptors. The discussed scheme combines granular computing algorithms with assumptions of a cellular automata traffic model. It enables direct determination of temporal characteristics for the recognised and extracted traffic states. The traffic parameters prediction algorithm was introduced that allow determining the sampling time intervals of the video detection system.
topic digital video-camera
granular computing algorithms
cellular automata traffic model
url http://www.transportproblems.polsl.pl/pl/Archiwum/2009/zeszyt1/2009t4z1_07.pdf
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