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Connected vehicle and driver's assistance applications are greatlyfacilitated by Enhanced Digital Maps (EDMs) that represent roadway features(e.g., lane edges or centerlines, stop bars). Due to the large number ofsignalized intersections and miles of roadway, manual development of EDMs on aglobal basis is not feasible. Mobile Terrestrial Laser Scanning (MTLS) is thepreferred data acquisition method to provide data for automated EDMdevelopment. Such systems provide an MTLS trajectory and a point cloud for theroadway environment. The challenge is to automatically convert these data intoan EDM. This article presents a new processing and feature extraction method,experimental demonstration providing SAE-J2735 map messages for eleven exampleintersections, and a discussion of the results that points out remainingchallenges and suggests directions for future research.

Challenges in Partially-Automated Roadway Feature Mapping Using Mobile Laser Scanning and Vehicle Trajectory Data