A precise proximity-weight formulation for map matching algorithms

With the increased use of satellite-based navigation devices in civilian vehicles, map matching (MM) studies have increased considerably in the past decade. Frequency of the data, and denseness of the underlying road network still dictate the accuracy limits of current MM algorithms. One practical way that can improve the accuracy of most MM approaches is to use more precise weights for the candidate road segments. Because of the geometric nature of the MM problem, proximity-weights have been considered in almost every MM study. However, being formulated through the shortest distance measure, these weights are prone to inaccuracies. We propose a new, more precise, proximity-weight formulation based on a cumulative proximity function which only assumes that the positioning data displays Gaussian distribution errors. Proposed formulations are developed independent of any MM approach, and for this reason they can be used easily under any future MM algorithm.