Convoy Detection using Sequence Alignment
Kai Li, Mark M. McKenney · 2019
In this paper, we investigate methods to detect convoys in trajectory data with locations sampled at irregular time intervals. In such cases, convoys that exist may not be detected in some algorithms. We explore three methods, one that involves adding interpolated points to trajectories, one that introduces flexibility to the temporal dimension, and one that uses sequence alignment. The algorithms are evaluated against a real-world data set.