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dc.contributor.authorSteiner, Albert-
dc.contributor.authorLeonhardt, Axel-
dc.date.accessioned2018-12-07T08:13:31Z-
dc.date.available2018-12-07T08:13:31Z-
dc.date.issued2011-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/13639-
dc.description.abstractProviding 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.de_CH
dc.language.isoende_CH
dc.publisherTransportation Research Boardde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectTRBde_CH
dc.subjectMap generationde_CH
dc.subjectTrafficde_CH
dc.subjectFloating car datade_CH
dc.subject.ddc370: Bildung und Erziehungde_CH
dc.titleMap-generation algorithm using low-frequency vehicle position datade_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
zhaw.publisher.placeWashingtonde_CH
zhaw.conference.details90th Annual Meeting of the Transportation Research Board, Washington, USA, 23-27 January 2011de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end17de_CH
zhaw.pages.start1de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsTRB 90th Annual Meeting Compendium of Papersde_CH
zhaw.webfeedDigital Mobilityde_CH
Appears in collections: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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