Road information, like lanes number, play an important role for intelligent vehicles (IV). Traditionally such road information are obtained through a vision-based measurement or by using a digital detailed map. In this paper, we present a new method for estimating the number of lanes using a low precision GPS receiver and OpenSteetMap (OSM). The method includes the integration of the GPS traces and OSM for a map matching. To this end we developed a probabilistic multicriteria algorithm for map matching that takes into account the accuracy of the GPS data and the attribute information of the road from OSM. Afterward we estimate the number of lanes from OSM. We tested our algorithm on a set of GPS data collected in an urban area near Paris for a total distance of 50km and the overall estimation accuracy reached 83.64%