Incremental Navigation Map Enhancement with GPS Tracks from Heterogeneous Sources

Michal Vesely; Clemens Novak; Andreas Reh; Herwig Mayr

Incremental Navigation Map Enhancement with GPS Tracks from Heterogeneous Sources

Michal Vesely, Clemens Novak, Andreas Reh, Herwig Mayr

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag

3 Zitate (Scopus)

Abstract

This contribution describes our approach to incremental navigation map generation and enhancement based on Global Positioning System (GPS) track data gathered through tracing the paths of entities with heterogeneous mobility models (e.g., pedestrians, bicyclists, cars, etc.). Our generic prototypical implementation is able to generate navigable maps from scratch as well as to enhance existing maps by deriving changes in the original map from the GPS tracks input, and to offer map updates for public download. For the core functionality of incremental semi-automatic map learning, a proprietary graph matching algorithm is combined with a set of models that take the varieties of input data into consideration. Areas of application comprise the continuous enhancement of navigation systems, their personalized adaptation, optimization of fleet management, and the generation of integral harmonized navigation data from heterogeneous sources.

Originalsprache	Englisch
Titel	Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications
Herausgeber (Verlag)	CSREA Press
Seiten	787-793
Seitenumfang	7
ISBN (Print)	1601320728, 9781601320728
Publikationsstatus	Veröffentlicht - 2008
Veranstaltung	Worldcomp 08 - The 2008 World Congress in Computer Science, Computer Engineering and Applied Computing - Las Vegas, USA/Vereinigte Staaten Dauer: 14 Juli 2008 → 17 Juli 2008 http://www.world-academy-of-science.org/worldcomp08/ws

Publikationsreihe

Name	Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications

Konferenz

Konferenz	Worldcomp 08 - The 2008 World Congress in Computer Science, Computer Engineering and Applied Computing
Land/Gebiet	USA/Vereinigte Staaten
Ort	Las Vegas
Zeitraum	14.07.2008 → 17.07.2008
Internetadresse	http://www.world-academy-of-science.org/worldcomp08/ws

Schlagwörter

graph learning
graph matching
digital map
incremental update
GPS

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Vesely, M., Novak, C., Reh, A., & Mayr, H. (2008). Incremental Navigation Map Enhancement with GPS Tracks from Heterogeneous Sources. in Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications (S. 787-793). (Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications). CSREA Press.

Vesely, Michal ; Novak, Clemens ; Reh, Andreas et al. / Incremental Navigation Map Enhancement with GPS Tracks from Heterogeneous Sources. Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications. CSREA Press, 2008. S. 787-793 (Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications).

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title = "Incremental Navigation Map Enhancement with GPS Tracks from Heterogeneous Sources",

abstract = "This contribution describes our approach to incremental navigation map generation and enhancement based on Global Positioning System (GPS) track data gathered through tracing the paths of entities with heterogeneous mobility models (e.g., pedestrians, bicyclists, cars, etc.). Our generic prototypical implementation is able to generate navigable maps from scratch as well as to enhance existing maps by deriving changes in the original map from the GPS tracks input, and to offer map updates for public download. For the core functionality of incremental semi-automatic map learning, a proprietary graph matching algorithm is combined with a set of models that take the varieties of input data into consideration. Areas of application comprise the continuous enhancement of navigation systems, their personalized adaptation, optimization of fleet management, and the generation of integral harmonized navigation data from heterogeneous sources.",

keywords = "graph learning, graph matching, digital map, incremental update, GPS, graph learning, graph matching, digital map, incremental update, GPS, Graph learning, Digital map, Incremental update, Graph matching",

author = "Michal Vesely and Clemens Novak and Andreas Reh and Herwig Mayr",

year = "2008",

language = "English",

isbn = "1601320728",

series = "Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications",

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pages = "787--793",

booktitle = "Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications",

note = "Worldcomp 08 - The 2008 World Congress in Computer Science, Computer Engineering and Applied Computing ; Conference date: 14-07-2008 Through 17-07-2008",

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Vesely, M, Novak, C, Reh, A & Mayr, H 2008, Incremental Navigation Map Enhancement with GPS Tracks from Heterogeneous Sources. in Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications. Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications, CSREA Press, S. 787-793, Worldcomp 08 - The 2008 World Congress in Computer Science, Computer Engineering and Applied Computing, Las Vegas, USA/Vereinigte Staaten, 14.07.2008.

Incremental Navigation Map Enhancement with GPS Tracks from Heterogeneous Sources. / Vesely, Michal; Novak, Clemens; Reh, Andreas et al.
Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications. CSREA Press, 2008. S. 787-793 (Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications).

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag

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AU - Vesely, Michal

AU - Novak, Clemens

AU - Reh, Andreas

AU - Mayr, Herwig

PY - 2008

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N2 - This contribution describes our approach to incremental navigation map generation and enhancement based on Global Positioning System (GPS) track data gathered through tracing the paths of entities with heterogeneous mobility models (e.g., pedestrians, bicyclists, cars, etc.). Our generic prototypical implementation is able to generate navigable maps from scratch as well as to enhance existing maps by deriving changes in the original map from the GPS tracks input, and to offer map updates for public download. For the core functionality of incremental semi-automatic map learning, a proprietary graph matching algorithm is combined with a set of models that take the varieties of input data into consideration. Areas of application comprise the continuous enhancement of navigation systems, their personalized adaptation, optimization of fleet management, and the generation of integral harmonized navigation data from heterogeneous sources.

AB - This contribution describes our approach to incremental navigation map generation and enhancement based on Global Positioning System (GPS) track data gathered through tracing the paths of entities with heterogeneous mobility models (e.g., pedestrians, bicyclists, cars, etc.). Our generic prototypical implementation is able to generate navigable maps from scratch as well as to enhance existing maps by deriving changes in the original map from the GPS tracks input, and to offer map updates for public download. For the core functionality of incremental semi-automatic map learning, a proprietary graph matching algorithm is combined with a set of models that take the varieties of input data into consideration. Areas of application comprise the continuous enhancement of navigation systems, their personalized adaptation, optimization of fleet management, and the generation of integral harmonized navigation data from heterogeneous sources.

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KW - graph matching

KW - digital map

KW - incremental update

KW - GPS

KW - graph learning

KW - graph matching

KW - digital map

KW - incremental update

KW - GPS

KW - Graph learning

KW - Digital map

KW - Incremental update

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M3 - Conference contribution

SN - 1601320728

SN - 9781601320728

T3 - Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications

SP - 787

EP - 793

BT - Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications

PB - CSREA Press

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ER -

Vesely M, Novak C, Reh A, Mayr H. Incremental Navigation Map Enhancement with GPS Tracks from Heterogeneous Sources. in Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications. CSREA Press. 2008. S. 787-793. (Proceedings of the 2008 International Conference on Artificial Intelligence, ICAI 2008 and Proceedings of the 2008 International Conference on Machine Learning; Models, Technologies and Applications).

Incremental Navigation Map Enhancement with GPS Tracks from Heterogeneous Sources

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