A Novel Map Matching Algorithm

Abstract

Presently, most of the researches on Map Matching focus on high sampling rate and accurate GPS points. This paper discusses a challenging problem with low GPS sampling rate and some continuous points with large deviation. To solve the problem efficiently, a novel matching method named F&PT is proposed. Firstly we employ a new method to generate sets of candidate roads. The GPS error analysis based on points is translated into based on roads. Secondly, a local strategy based on potential real trajectories is applied to solve the core problem of selecting an optimal road from the sets which contain only two candidate roads. In this approach, we consider not only the spatial location information and orientation angle information but also the influence of local points on the matching point from a new sight. We evaluate our method based on a real trajectory dataset. The experiments show that the proposed method has a higher accuracy compared with the related methods, e.g. ST-matching algorithm and IVMM algorithm, when the sampling interval is less than 210s.