Article
Segmenting human trajectory data by movement states while addressing signal loss and signal noise
International Journal of Geographical Information Science
(2018)
Abstract
This paper considers the problem of partitioning an individual GPS
trajectory data into homogeneous, meaningful segments such as
stops and trips. Signal loss and signal noise are highly prevalent in
human trajectory data, and it is challenging to deal with uncertainties
in segmentation algorithms. We propose a new trajectory
segmentation algorithm that detects stop segments in a noiserobust
manner from GPS data with time gaps. The algorithm consists
of three steps that impute time gaps, split data into base
segments and estimate states over a base segment. The statedependent
path interpolation was proposed as a framework for
gap imputation to deal with locational and temporal uncertainties
associated with signal loss. A spatiotemporal clustering-based trajectory
segmentation was proposed to detect spatiotemporal clusters
of any shape regardless of density to cut a trajectory into
internally similar base segments. Fuzzy inference was employed to
deal with borderline cases in determining states over base segments
based on input features. The proposed algorithm was
applied to detect stop/move episodes from raw GPS trajectories
that were collected from 20 urban and 19 suburban participants.
Sensitivity analysis was conducted to guide the choice of parameters
such as the temporal and spatial definitions of a stop.
Experimentation results show that the proposed method correctly
identified 92% of stop/move episodes, and correctly estimated 98%
of episode duration. This study indicates that a sequence of statedependent
gap imputation, clustering-based data segmentation
and fuzzy-set-based state estimation can satisfactorily deal with
uncertainty in processing human GPS trajectory data.
Keywords
- Uncertain trajectories,
- stop detection,
- GPS,
- path interpolation,
- fuzzy inference
Disciplines
Publication Date
2018
DOI
10.1080/13658816.2018.1423685
Citation Information
Sungsoon Hwang, Cynthia VanDeMark, Navdeep Dhatt, Sai Yalla, et al.. "Segmenting human trajectory data by movement states while addressing signal loss and signal noise" International Journal of Geographical Information Science (2018) Available at: http://works.bepress.com/sungsoon_hwang/25/