Mining GPS Traces for Map Refinement
Data Mining and Knowledge Discovery
Scalable, Distributed, Real-Time Map Generation
IEEE Pervasive Computing
Mining Traffic Condition from Trajectories
FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04
OpenStreetMap: User-Generated Street Maps
IEEE Pervasive Computing
From GPS traces to a routable road map
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Road extraction using smart phones GPS
Proceedings of the 2nd International Conference on Computing for Geospatial Research & Applications
Data-driven trajectory smoothing
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Mining large-scale, sparse GPS traces for map inference: comparison of approaches
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
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GPS traces can track actual time and coordinates of regular vehicles going their own business, and it is easy to scale to the entire area with an accuracy of 6 to 10 meters in normal condition. As a result, extracting road map from GPS traces could be an alternative way to traditional way of road map generation. The basic idea of this paper is to describe a process which incrementally improves existing road data with incoming new information in terms of GPS traces. In this way we consider the GPS traces as measurements which represent a "digitization" of the true road. Although the accuracy of the traces is not too high, due to the high number of measurements an improvement of the quality of the road information can be achieved. Thus, this paper presents a method for integrating GPS traces and an existing out of copyright road map towards a more accurate, up-to-data and detailed road map. First we profile the existing road by a sequence of perpendicular lines and get the road's candidate sampling traces which intersect with the profile. Then we match the potential traces with the road and finally estimate the new road centerline from its corresponding traces. In addition to the geometry of roads we also mine attribute information from GPS traces, such as number of lanes and turning restrictions of the roads.