ROAD MESH MODELLING USING THE SPATIOTEMPORAL CLUSTERIZATION

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00171806" target="_blank" >RIV/68407700:21230/10:00171806 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21240/10:00171806
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
ROAD MESH MODELLING USING THE SPATIOTEMPORAL CLUSTERIZATION
Original language description
The GPS navigation is widely used aid for travelers. However, good navigation depends on good maps, which are sometimes hard to get. In this paper we explore a method to model a road mesh using self-organizing spatiotemporal data clustering of collectedGPS data. The resulting road mesh model is obtained from simulated self organizing neural network, which clusters the individual data vectors and infers the time dependencies between the clusters. This allows to detect one way roads, or slow traffic automatically. To achive this goal we model the road mesh with the Temporal Hebbian Self-organizing map (THSOM). This paper presents a novel training method for the simulated THSOM neural network, which reduces training period and improves model the convergence of original THSOM neural network. The road mesh model is obtained from real GPS data as well as from simulated data set.
Czech name
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Czech description
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Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 7th EUROSIM Congress on Modelling and Simulation, Vol. 2: Full Papers
ISBN
978-80-01-04589-3
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
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Publisher name
Department of Computer Science and Engineering, FEE, CTU in Prague
Place of publication
Prague
Event location
Praha
Event date
Sep 6, 2010
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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