Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-4/W25, 87-93, 2011
https://doi.org/10.5194/isprsarchives-XXXVIII-4-W25-87-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
30 Aug 2012
MULTI-STAGE APPROACH TO TRAVEL-MODE SEGMENTATION AND CLASSIFICATION OF GPS TRACES
L. Zhang, S. Dalyot, D. Eggert, and M. Sester Institut für Kartographie und Geoinformatik (IKG), Leibniz Universität Hannover, Appelstraße 9a, 30167 Hannover, Germany
Keywords: Acquisition, Data mining, Pattern, Recognition, Classification, GPS/INS, Segmentation, Mapping Abstract. This paper presents a multi-stage approach toward the robust classification of travel-modes from GPS traces. Due to the fact that GPS traces are often composed of more than one travel-mode, they are segmented to find sub-traces characterized as an individual travel-mode. This is conducted by finding individual movement segments by identifying stops. In the first stage of classification three main travel-mode classes are identified: pedestrian, bicycle, and motorized vehicles; this is achieved based on the identified segments using speed, acceleration and heading related parameters. Then, segments are linked up to form sub-traces of individual travel-mode. After the first stage is achieved, a breakdown classification of the motorized vehicles class is implemented based on sub-traces of individual travel-mode of cars, buses, trams and trains using Support Vector Machines (SVMs) method. This paper presents a qualitative classification of travel-modes, thus introducing new robust and precise capabilities for the problem at hand.
Conference paper (PDF, 1068 KB)


Citation: Zhang, L., Dalyot, S., Eggert, D., and Sester, M.: MULTI-STAGE APPROACH TO TRAVEL-MODE SEGMENTATION AND CLASSIFICATION OF GPS TRACES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-4/W25, 87-93, https://doi.org/10.5194/isprsarchives-XXXVIII-4-W25-87-2011, 2011.

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