Support Vector Machine Applied to Road Traffic Event Classification

Support Vector Machine Applied to Road Traffic Event Classification

The aim of this paper is to present results of road traffic event signal recognition. First, several types of systems for road traffic monitoring, including Intelligent Transport System (ITS) are shortly described. Then, assumptions of creating a database of vehicle signals recorded in different wea...

Full description

Bibliographic Details
Main Authors: Blaszke Maciej, Kostek Bozena
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201823104001
id doaj-3b085d5f98b54773aad5d3250b42e08c
record_format Article
spelling doaj-3b085d5f98b54773aad5d3250b42e08c2021-02-02T05:49:11ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-012310400110.1051/matecconf/201823104001matecconf_gambit2018_04001Support Vector Machine Applied to Road Traffic Event ClassificationBlaszke MaciejKostek BozenaThe aim of this paper is to present results of road traffic event signal recognition. First, several types of systems for road traffic monitoring, including Intelligent Transport System (ITS) are shortly described. Then, assumptions of creating a database of vehicle signals recorded in different weather and road conditions are outlined. Registered signals were edited as single vehicle pass by. Using the Matlab-based application a feature vector containing 48 parameters was extracted and analyzed in the context of parameter separability and classification effectiveness employing SVM (Support Vector Machine) algorithm. In conclusion, the classifier developed and its effectiveness were discussed.https://doi.org/10.1051/matecconf/201823104001
collection DOAJ
language English
format Article
sources DOAJ
author Blaszke Maciej
Kostek Bozena
spellingShingle Blaszke Maciej
Kostek Bozena
Support Vector Machine Applied to Road Traffic Event Classification
MATEC Web of Conferences
author_facet Blaszke Maciej
Kostek Bozena
author_sort Blaszke Maciej
title Support Vector Machine Applied to Road Traffic Event Classification
title_short Support Vector Machine Applied to Road Traffic Event Classification
title_full Support Vector Machine Applied to Road Traffic Event Classification
title_fullStr Support Vector Machine Applied to Road Traffic Event Classification
title_full_unstemmed Support Vector Machine Applied to Road Traffic Event Classification
title_sort support vector machine applied to road traffic event classification
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2018-01-01
description The aim of this paper is to present results of road traffic event signal recognition. First, several types of systems for road traffic monitoring, including Intelligent Transport System (ITS) are shortly described. Then, assumptions of creating a database of vehicle signals recorded in different weather and road conditions are outlined. Registered signals were edited as single vehicle pass by. Using the Matlab-based application a feature vector containing 48 parameters was extracted and analyzed in the context of parameter separability and classification effectiveness employing SVM (Support Vector Machine) algorithm. In conclusion, the classifier developed and its effectiveness were discussed.
url https://doi.org/10.1051/matecconf/201823104001
work_keys_str_mv AT blaszkemaciej supportvectormachineappliedtoroadtrafficeventclassification
AT kostekbozena supportvectormachineappliedtoroadtrafficeventclassification
_version_ 1724302627517235200

Similar Items