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Zhang, Lijuan; Dalyot, Sagi; Eggert, Daniel; Sester, Monika (2011)
Publisher: Copernicus GmbH
Languages: English
Types: Article
Subjects: Mapping, GPS/INS, TA1501-1820, Data mining, Pattern, Recognition, Engineering (General). Civil engineering (General), Technology, Classification, TA1-2040, system, T, Geowissenschaften, Applied optics. Photonics, Segmentation, Acquisition
ddc: ddc:550
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.
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