Map matching accuracy: Energy efficient location sampling using smartphones

Abstract

Map matching is the process of positioning each point of a mobility trajectory on a digital map. A mobility trajectory is nothing more than a sequence of points characterized by latitude, longitude and timestamp information. The difficulty of map-matching depends on various factors such as the accuracy of maps, or the sampling rate of the points of the trajectory. In this paper, we explore the different tradeoffs involved in map-matching, and analyze how these vary under different location sampling conditions. We propose an algorithm to efficiently adapt the sampling method of the user location in order to reduce the energy consumption over the mobile device, while ensuring a sufficient reliability of the reconstructed path. Finally, we validate the proposed approach over real-world data, showing a 23% energy reduction in various mobility conditions, while maintaining a high accuracy of the reconstructed path.