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A novel map-matching algorithm to improve vehicle tracking system accuracy

The satellite-based Vehicle Tracking System accuracy can be improved by augmenting the positional information using road network data, in a process known as map-matching. Map-matching algorithms attempt to pinpoint the vehicle in a particular road map segment (or any restricting track such as rails,...

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Main Authors: A.M., Said, A.N., Matori, A., Dewandaru
Format: Conference or Workshop Item
Published: 2007
Subjects:
Q Science (General)
QA75 Electronic computers. Computer science
Online Access:http://eprints.utp.edu.my/121/1/paper.pdf
http://www.scopus.com/inward/record.url?eid=2-s2.0-57949111197&partnerID=40&md5=11651981fb20bd107bd485de878c48c7
http://eprints.utp.edu.my/121/
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spelling my.utp.eprints.1212017-01-19T08:26:59Z A novel map-matching algorithm to improve vehicle tracking system accuracy A.M., Said A.N., Matori A., Dewandaru Q Science (General) QA75 Electronic computers. Computer science The satellite-based Vehicle Tracking System accuracy can be improved by augmenting the positional information using road network data, in a process known as map-matching. Map-matching algorithms attempt to pinpoint the vehicle in a particular road map segment (or any restricting track such as rails, etc), in spite of the digital map errors and navigation system inaccuracies. Point-to-curve matching algorithm is not suitable to the problem since it ignores any historical data and often gave unstable, jumping results. The better curve-to-curve matching algorithms considers the road connectivity and measure the similarity between track and the possible road path (hypotheses), but mostly does not have any way to manage multiple track hypotheses which have varying degree of similarity over time. The paper presents a new similarity metric for curve-to-curve map-matching technique, combined with the ability to maintain many possible road hypotheses and picks the most likely hypothesis at a time, enabling future corrections if necessary, therefore providing intelligent guesses with considerable accuracy. ©2007 IEEE. 2007 Conference or Workshop Item NonPeerReviewed application/pdf http://eprints.utp.edu.my/121/1/paper.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-57949111197&partnerID=40&md5=11651981fb20bd107bd485de878c48c7 A.M., Said and A.N., Matori and A., Dewandaru (2007) A novel map-matching algorithm to improve vehicle tracking system accuracy. In: 2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007, 25 November 2007 through 28 November 2007, Kuala Lumpur. http://eprints.utp.edu.my/121/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic Q Science (General)
QA75 Electronic computers. Computer science
spellingShingle Q Science (General)
QA75 Electronic computers. Computer science
A.M., Said
A.N., Matori
A., Dewandaru
A novel map-matching algorithm to improve vehicle tracking system accuracy
description The satellite-based Vehicle Tracking System accuracy can be improved by augmenting the positional information using road network data, in a process known as map-matching. Map-matching algorithms attempt to pinpoint the vehicle in a particular road map segment (or any restricting track such as rails, etc), in spite of the digital map errors and navigation system inaccuracies. Point-to-curve matching algorithm is not suitable to the problem since it ignores any historical data and often gave unstable, jumping results. The better curve-to-curve matching algorithms considers the road connectivity and measure the similarity between track and the possible road path (hypotheses), but mostly does not have any way to manage multiple track hypotheses which have varying degree of similarity over time. The paper presents a new similarity metric for curve-to-curve map-matching technique, combined with the ability to maintain many possible road hypotheses and picks the most likely hypothesis at a time, enabling future corrections if necessary, therefore providing intelligent guesses with considerable accuracy. ©2007 IEEE.
format Conference or Workshop Item
author A.M., Said
A.N., Matori
A., Dewandaru
author_facet A.M., Said
A.N., Matori
A., Dewandaru
author_sort A.M., Said
title A novel map-matching algorithm to improve vehicle tracking system accuracy
title_short A novel map-matching algorithm to improve vehicle tracking system accuracy
title_full A novel map-matching algorithm to improve vehicle tracking system accuracy
title_fullStr A novel map-matching algorithm to improve vehicle tracking system accuracy
title_full_unstemmed A novel map-matching algorithm to improve vehicle tracking system accuracy
title_sort novel map-matching algorithm to improve vehicle tracking system accuracy
publishDate 2007
url http://eprints.utp.edu.my/121/1/paper.pdf
http://www.scopus.com/inward/record.url?eid=2-s2.0-57949111197&partnerID=40&md5=11651981fb20bd107bd485de878c48c7
http://eprints.utp.edu.my/121/
_version_ 1738655028972879872
score 13.211869

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