Extraction of bicycle commuter trips from day-long GPS trajectories

Gerald Richter (Vortragende:r), Christian Rudloff, Anita Graser

Publikation: Beitrag in Buch oder TagungsbandVortrag mit Beitrag in Tagungsband


Collected GPS data often lacks metadata (e.g. mode of transport information) and is noisy (e.g. due to longer stops and bad GPS reception). Several measures are necessary to pre-process GPS data in order to detect trip starts and ends as well as modes of transport. These measures comprise segmentation (splitting of tracks into trips) and outlier removal. In this paper, previously developed methods implementing such algorithms and their application to the provided set of CDC2013 cyclist commuter tracks are presented. Mode detection is applied to the trips subsequently in order to separate bicycle trips from trips by other modes of transport (e.g. walking the bike). The processing results are evaluated by comparison against provided cleaned reference data. Some statistical properties of the resulting tracks are shown.
TitelUnderstanding urban cycling: A data challenge (CDC2013) - Proceedings of abstracts
PublikationsstatusVeröffentlicht - 2013
VeranstaltungUnderstanding urban cycling: A data challenge (CDC2013) -
Dauer: 14 Mai 2013 → …


KonferenzUnderstanding urban cycling: A data challenge (CDC2013)
Zeitraum14/05/13 → …

Research Field

  • Ehemaliges Research Field - Mobility Systems


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