A novel algorithm of low sampling rate GPS trajectories on map-matching

Abstract

Map-matching is the process of matching the GPS locus to the road network on the digital map. However, due to the most existing map-matching algorithms that are based on high sampling rate, when the sampling interval is increased, the correct rate of the algorithm will be greatly reduced. Based on this, this paper proposed a new algorithm of map-matching for low sampling rate GPS trajectories. The algorithm gave full consideration to the road network of the geometric structure and topological structure and the mutual influence between adjacent points (time, speed information) by calculating the probability of each trajectory point of candidate points to determine matching results. At the end of this paper, we use the data of Beijing UCAR Inc.’s car in a case study. This case demonstrates: For low sampling rate matching track points in the complex road, the algorithm has a good uptime, and an exact match was found.