We propose a point segmentation and grouping method to generate road maps from GPS traces. First, we present a progressive point cloud segmentation algorithm based on Total Least Squares (TLS) line fitting. Second, we group topologically connected point clusters by the point's orientation and cluster's spatial proximity, where the topological relationship is generated using Hidden Markov Model (HMM) map matching. Finally, we refine the intersections of roads so that their geometrical and topological relationships are consistent with each other. Experimental results show that our algorithm is robust to noises and the generated road network has a high accuracy in terms of geometry and topology. Compare to the representative algorithms; the results of our new algorithm have a higher F-measure score for different matching thresholds.
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