At an abstract level, this paper addresses the problem of taking an existing knowledge structure, the digital map, and augmenting it with additional information, the lane models. If we view the digital map as a theory describing the actual roadways, then adding lane models refines the theory, making it more accurate and complete. Our approach combines the strengths of theory revision and automated mapping research to take advantage of existing knowledge while processing large amounts of unlabelled real-world data.