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Detecting Urban Transport Modes Using a Hybrid Knowledge Driven Framework from GPS Trajectory
2016
ISPRS International Journal of Geo-Information
Transport mode information is essential for understanding people's movement behavior and travel demand estimation. Current approaches extract travel information once the travel is complete. Such approaches are limited in terms of generating just-in-time information for a number of mobility based applications, e.g., real time mode specific patronage estimation. In order to detect the transport modalities from GPS trajectories, various machine learning approaches have already been explored.
doi:10.3390/ijgi5110207
fatcat:mdhmsldpqzftnm7g3ebpxypkky