Accurate Discovery of Valid Convoys from Moving Object Trajectories

Abstract

Given a set of moving object trajectories, it is of interest to find a group of objects, called a convoy, that are spatially density-connected for a certain duration of time. However, existing convoy discovery algorithms have a critical problem of accuracy; they tend to both miss larger convoys and retrieve invalid ones where the density-connectivity among the objects is not completely satisfied. We propose a new valid convoy discovery algorithm, called VCoDA, for the accurate discovery of valid convoys from moving object trajectories. Specifically, VCoDA first retrieves all partially connected convoys while guaranteeing no false dismissal of any valid convoys and then validates their density-connectivity to eventually obtain a complete set of valid convoys. Our extensive experiments on three real-world datasets demonstrate the effectiveness of our technique; VCoDA improves the precision by a factor of 3 on average and the recall by up to 2 orders of magnitude as compared to an existing method.