Details
Originalsprache | Englisch |
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Titel des Sammelwerks | 3rd ACM SIGSPATIAL International Workshop on Computational Transportation Science 2010, IWCTS 2010 - In conjunction with ACM SIGSPATIAL GIS 2010 |
Seiten | 17-22 |
Seitenumfang | 6 |
ISBN (elektronisch) | 9781450304290 |
Publikationsstatus | Veröffentlicht - 2 Nov. 2010 |
Veranstaltung | 3rd ACM SIGSPATIAL International Workshop on Computational Transportation Science, IWCTS 2010 - San Jose, USA / Vereinigte Staaten Dauer: 2 Nov. 2010 → … |
Publikationsreihe
Name | 3rd ACM SIGSPATIAL International Workshop on Computational Transportation Science 2010, IWCTS 2010 - In conjunction with ACM SIGSPATIAL GIS 2010 |
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Abstract
GPS traces can track actual time and coordinates of regular vehicles going their own business, and it is easy to scale to the entire area with an accuracy of 6 to 10 meters in normal condition. As a result, extracting road map from GPS traces could be an alternative way to traditional way of road map generation. The basic idea of this paper is to describe a process which incrementally improves existing road data with incoming new information in terms of GPS traces. In this way we consider the GPS traces as measurements which represent a "digitization" of the true road. Although the accuracy of the traces is not too high, due to the high number of measurements an improvement of the quality of the road information can be achieved. Thus, this paper presents a method for integrating GPS traces and an existing out of copyright road map towards a more accurate, up-to-data and detailed road map. First we profile the existing road by a sequence of perpendicular lines and get the road's candidate sampling traces which intersect with the profile. Then we match the potential traces with the road and finally estimate the new road centerline from its corresponding traces. In addition to the geometry of roads we also mine attribute information from GPS traces, such as number of lanes and turning restrictions of the roads.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Angewandte Informatik
- Informatik (insg.)
- Computernetzwerke und -kommunikation
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
- Sozialwissenschaften (insg.)
- Verkehr
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- Apa
- Vancouver
- BibTex
- RIS
3rd ACM SIGSPATIAL International Workshop on Computational Transportation Science 2010, IWCTS 2010 - In conjunction with ACM SIGSPATIAL GIS 2010. 2010. S. 17-22 (3rd ACM SIGSPATIAL International Workshop on Computational Transportation Science 2010, IWCTS 2010 - In conjunction with ACM SIGSPATIAL GIS 2010).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Integration of GPS traces with road map
AU - Zhang, Lijuan
AU - Thiemann, Frank
AU - Sester, Monika
PY - 2010/11/2
Y1 - 2010/11/2
N2 - GPS traces can track actual time and coordinates of regular vehicles going their own business, and it is easy to scale to the entire area with an accuracy of 6 to 10 meters in normal condition. As a result, extracting road map from GPS traces could be an alternative way to traditional way of road map generation. The basic idea of this paper is to describe a process which incrementally improves existing road data with incoming new information in terms of GPS traces. In this way we consider the GPS traces as measurements which represent a "digitization" of the true road. Although the accuracy of the traces is not too high, due to the high number of measurements an improvement of the quality of the road information can be achieved. Thus, this paper presents a method for integrating GPS traces and an existing out of copyright road map towards a more accurate, up-to-data and detailed road map. First we profile the existing road by a sequence of perpendicular lines and get the road's candidate sampling traces which intersect with the profile. Then we match the potential traces with the road and finally estimate the new road centerline from its corresponding traces. In addition to the geometry of roads we also mine attribute information from GPS traces, such as number of lanes and turning restrictions of the roads.
AB - GPS traces can track actual time and coordinates of regular vehicles going their own business, and it is easy to scale to the entire area with an accuracy of 6 to 10 meters in normal condition. As a result, extracting road map from GPS traces could be an alternative way to traditional way of road map generation. The basic idea of this paper is to describe a process which incrementally improves existing road data with incoming new information in terms of GPS traces. In this way we consider the GPS traces as measurements which represent a "digitization" of the true road. Although the accuracy of the traces is not too high, due to the high number of measurements an improvement of the quality of the road information can be achieved. Thus, this paper presents a method for integrating GPS traces and an existing out of copyright road map towards a more accurate, up-to-data and detailed road map. First we profile the existing road by a sequence of perpendicular lines and get the road's candidate sampling traces which intersect with the profile. Then we match the potential traces with the road and finally estimate the new road centerline from its corresponding traces. In addition to the geometry of roads we also mine attribute information from GPS traces, such as number of lanes and turning restrictions of the roads.
KW - GPS data
KW - Incremental refinement
KW - Integration
KW - Road map
UR - http://www.scopus.com/inward/record.url?scp=85012024685&partnerID=8YFLogxK
U2 - 10.1145/1899441.1899447
DO - 10.1145/1899441.1899447
M3 - Conference contribution
AN - SCOPUS:85012024685
T3 - 3rd ACM SIGSPATIAL International Workshop on Computational Transportation Science 2010, IWCTS 2010 - In conjunction with ACM SIGSPATIAL GIS 2010
SP - 17
EP - 22
BT - 3rd ACM SIGSPATIAL International Workshop on Computational Transportation Science 2010, IWCTS 2010 - In conjunction with ACM SIGSPATIAL GIS 2010
T2 - 3rd ACM SIGSPATIAL International Workshop on Computational Transportation Science, IWCTS 2010
Y2 - 2 November 2010
ER -