| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Map-generation algorithm using low-frequency vehicle position data |
| Autor/-in: | Steiner, Albert Leonhardt, Axel |
| Tagungsband: | TRB 90th Annual Meeting Compendium of Papers |
| Seite(n): | 1 |
| Seiten bis: | 17 |
| Angaben zur Konferenz: | 90th Annual Meeting of the Transportation Research Board, Washington, USA, 23-27 January 2011 |
| Erscheinungsdatum: | 2011 |
| Verlag / Hrsg. Institution: | Transportation Research Board |
| Verlag / Hrsg. Institution: | Washington |
| Sprache: | Englisch |
| Schlagwörter: | TRB; Map generation; Traffic; Floating car data |
| Fachgebiet (DDC): | 370: Bildung und Erziehung |
| Zusammenfassung: | Providing accurate map data is essential for a variety of applications in traffic engineering, e.g. navigation systems. To overcome costs and effort associated with classical map generation methods (e.g. surveying or specialized vehicles) a method for automatic map generation based on position data stemming from vehicle fleets that are already equipped with GPS and participate in day-to-day traffic is presented. The method is designed in particular for urban road networks, where building work is carried out frequently. In this paper we make use of taxi fleet data for map generation. The data used were recorded at relatively low frequencies (15 to 90 seconds), such that a trivial connection of subsequent positions is not possible. The problem is solved by processing the data through a series of algorithmic steps. After data cleaning and transforming raw data by a Transverse Mercator projection to a plane, density regions based on geographic position and estimated headings are calculated. The density images are filtered by a Gaussian kernel and a watershed transform is applied. From the resulting image a skeleton is derived and intersections are detected by dedicated rules. The resulting directed graph is compared with aerial images from Google Earth and an existing OpenStreetMap digital road network. Using data from vehicles participating in day-to-day traffic allows not only to derive static network information (nodes / links), but - depending on the vehicle fleet used - to annotate the resulting graph with attributes directly deduced from data, like typical link speed distributions or turning fractions at intersections. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/13639 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Datenanalyse und Prozessdesign (IDP) |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
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Steiner, A., & Leonhardt, A. (2011). Map-generation algorithm using low-frequency vehicle position data [Conference paper]. TRB 90th Annual Meeting Compendium of Papers, 1–17.
Steiner, A. and Leonhardt, A. (2011) ‘Map-generation algorithm using low-frequency vehicle position data’, in TRB 90th Annual Meeting Compendium of Papers. Washington: Transportation Research Board, pp. 1–17.
A. Steiner and A. Leonhardt, “Map-generation algorithm using low-frequency vehicle position data,” in TRB 90th Annual Meeting Compendium of Papers, 2011, pp. 1–17.
STEINER, Albert und Axel LEONHARDT, 2011. Map-generation algorithm using low-frequency vehicle position data. In: TRB 90th Annual Meeting Compendium of Papers. Conference paper. Washington: Transportation Research Board. 2011. S. 1–17
Steiner, Albert, and Axel Leonhardt. 2011. “Map-Generation Algorithm Using Low-Frequency Vehicle Position Data.” Conference paper. In TRB 90th Annual Meeting Compendium of Papers, 1–17. Washington: Transportation Research Board.
Steiner, Albert, and Axel Leonhardt. “Map-Generation Algorithm Using Low-Frequency Vehicle Position Data.” TRB 90th Annual Meeting Compendium of Papers, Transportation Research Board, 2011, pp. 1–17.
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