Vehicle Trajectory Enhanced Map-Matching Method for Low Frequency GPS Data

The GPS map matching technique matches a series of geographic coordinates to a road network. However, most existing algorithms mainly consider the geometric and topological relationships of the GPS observations, disregarding information in the historical floating data. This study developed an enhanced spatial-temporal matching (EST-matching) algorithm effective with low frequency GPS data. The proposed algorithm uses the possible minimum travel time to filter out the unrealistic route and build a graph of the candidate paths. (2) It considers the initial matching probability between candidates and the historical edge data to identify the actual vehicle route. (3) For vehicles at intersections, we introduce direction analysis to increase algorithm accuracy. The EST-matching algorithm was tested against the stMM algorithm to verify its performance at various data collection frequencies and matching radius. The proposed algorithm outperforms the stMM algorithm in terms of matching accuracy based low sampling frequencies, especially in central urban areas.