3,637 research outputs found

    Incremental data acquisition from gps-traces

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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 road map towards a more accurate, up-to-data and detailed road map. First we profile the existing road by a sequence of perpendicular profiles 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. Furthermore, we explore the benefit of an incremental acquisition by a temporal analysis of the data

    Enrichment of OpenStreetMap data completeness with sidewalk geometries using data mining techniques

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    Tailored routing and navigation services utilized by wheelchair users require certain information about sidewalk geometries and their attributes to execute efficiently. Except some minor regions/cities, such detailed information is not present in current versions of crowdsourced mapping databases including OpenStreetMap. CAP4Access European project aimed to use (and enrich) OpenStreetMap for making it fit to the purpose of wheelchair routing. In this respect, this study presents a modified methodology based on data mining techniques for constructing sidewalk geometries using multiple GPS traces collected by wheelchair users during an urban travel experiment. The derived sidewalk geometries can be used to enrich OpenStreetMap to support wheelchair routing. The proposed method was applied to a case study in Heidelberg, Germany. The constructed sidewalk geometries were compared to an official reference dataset ("ground truth dataset"). The case study shows that the constructed sidewalk network overlays with 96% of the official reference dataset. Furthermore, in terms of positional accuracy, a low Root Mean Square Error (RMSE) value (0.93 m) is achieved. The article presents our discussion on the results as well as the conclusion and future research directions
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