Online Map Matching Algorithm Using Segment Angle Based on Hidden Markov Model

The Global Positioning System(GPS) is used to find a specific point on the real earth although GPS positioning technology is becoming more and more mature, GPS always exists with equipment inherent errors or measurement methods errors. so map matching step is a very important preprocessing for lots of applications, such as traffic flow control, taxi mileage calculation, and finding some people. However, many current methods only deal with distance variables and do not handle angle variables between two segments. In this paper, we propose a new road network map matching algorithm, considering not only the distance between two sample points but also taking into account the angle between two candidate segments using the Hidden Markov Model (HMM) which is a popular solution for map matching. Subsequently, to solve the HMM problem, we make use of dynamic programming Viterbi algorithm to find the maximum probability road segments. The experiments are implemented on BEIJING CITY map real dataset and display that our map matching algorithm significantly improve the accuracy compared with ST-Matching global algorithm.