Enhancing digital maps to support reasoning on traffic sign compliance

Abstract

This article presents a new methodology of enriching digital maps in order to reason upon the traffic sign compliance, of traffic participants. The Open Street Map (OSM) data is augmented with a new layer for road orientation and road intersections in order to support not only map matching, but also reasoning processes on the compliance to traffic regulations provided by traffic signs. In order to increase the accuracy of the road map, traces collected with a high precision GPS receiver are used in a probabilistic model of traffic lanes. A distribution of points across the road relative to the existing OSM center-line is obtained by learning Gaussian Mixture Models. A method for extracting accurate position for static points is also proposed and applied for positions of traffic signs. The enhanced digital map is applied on the identification of car's percepts which support the rule based reasoning about traffic sign compliance.