Improvements of a Topological Map-Matching Algorithm in Post-Processing Mode

Abstract

The map-matching problem commonly arises when integrating position and other information from Global Navigation Satellite Systems (GNSS) such as GPS into a digital road map. This study presents improvements to an existing post-processing topological map-matching algorithm (TMMA) that successfully solves this problem. Both existing and improved TMMA were tested and compared regarding solution quality and computation time using GPS data collected from nine winter maintenance vehicle routes in Portage County, Wisconsin in the United States. On average, the results indicate an increase of 0.6% in the correct assignment of GPS points to the road network, and a decrease of 1% in the false negative (FN) cases (unmatched GPS points) when comparing the improved TMMA to the existing TMMA. Additionally, the improved TMMA can solve on average 1.3% more cases than the existing TMMA by assigning incorrect and FN points to correct road segments. Although enhanced results in terms of solution quality were obtained with the improved TMMA, the computation time is increased with this version of the TMMA due to additional steps that are incorporated in the resolution of the map-matching problem. Finally, the paired-sample T tests were conducted to identify statistical differences between both versions of the TMMA.