Multi-stage approach to travel-mode segmentation and classification of gps traces

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Multi-stage approach to travel-mode segmentation and classification of gps traces

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Zhang, Lijuan / Dalyot, Sagi / Eggert, Daniel / Sester, Monika

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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Dokumentinformationen

Titel :

Multi-stage approach to travel-mode segmentation and classification of gps traces

Beteiligte:

Zhang, Lijuan (Autor:in) / Dalyot, Sagi (Autor:in) / Eggert, Daniel (Autor:in) / Sester, Monika (Autor:in)

Erscheinungsdatum :

2011-01-01

Anmerkungen:

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences: [Geospatial Data Infrastructure: From Data Acquisition And Updating To Smarter Services] 38-4 (2011), Nr. W25

DOI :

https://doi.org/10.15488/1143

Medientyp :

Aufsatz (Zeitschrift)

Format :

Elektronische Ressource

Sprache :

Englisch

Schlagwörter :

Acquisition , Data mining , Pattern , Recognition , Classification , GPS/INS , Segmentation , Mapping , system , ddc:550 , Konferenzschrift