Collaborative Map Matching in Nav2Nav

Although in-car navigation systems are becoming commonplace, cars travelling in urban canyon areas still suffer from poor positional accuracy and limited visibility of GPS satellites due to signal blockage. As a result, map matching accuracy and navigation performance may not reach the required level for many applications. Researchers have tried to address positional inaccuracy in navigation systems using various techniques, such as map matching, augmentation, and differential GPS. However, some void still exist as these techniques require intensive computation, static base stations, or installation of extra equipment. In this paper, we propose Collaborative Map Matching (CMM) which is a novel technique aiming to improve map matching accuracy in Nav2Nav. CMM is based on differential GPS, high quality road map, and collaborative computation. CMM does not require intensive computation, static base stations, or extra equipment installed in cars. The main requirement is for cars to work collaboratively, through Nav2Nav, to help one another. Simulation of CMM shows that improved GPS positional accuracy obtained by one car can be shared to improve the map matching accuracy of other nearby cars.