An improved map-matching model for GPS data with low polling rates to track vehicles

To track a vehicle using GPS data, map matching is not only to select the map feature that the vehicle was at a GPS point, but also to find out the route it traveled. For GPS data at high polling rate, it is very obvious that the vehicle stays on the same map feature or a map feature directly connected with the previous GPS point. For low polling rates, a map feature where a vehicle is at a GPS point, is not always directly connected with the map feature where the vehicle is at the previous GPS point. In this paper, an improved model is proposed. The candidate set generation considers the difference of the width of links, and the matched map feature selection considers the length of the route, the difference between the azimuth of the GPS point and the map feature and the deviation of the raw GPS position to the candidate map feature. A field test shows that the improved model performs better than the previous model.