Map matching algorithm using interval analysis and Dempster-Shafer theory

The goal of map matching methods is to compute an accurate position of a vehicle from an initial estimated position using a digital road network data. In this paper, a new map matching method based on Dempster-Shafer theory and interval analysis is presented. The core idea of this method is the use of Dempster-Shafer theory for modeling partial information on model and measurement uncertainties and for managing multiple hypothesis situations. This technique proves to be relevant to treat junction roads situations or parallel roads. The results on simulated data show the usefulness of the proposed method.