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|Author:||Florian Jomrich, Daniel Bischoff, Steffen Knapp, Tobias Meuser, Björn Richerzhagen, Ralf Steinmetz|
|Kind:||In proceedings - use for conference & workshop papers|
|Journal:||In Proceedings of the International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS)|
|Keywords:||map change detection, low cost, smartphones, sensor fusion, lane change detection Abstract:|
|Abstract:||High Definition Street Maps (HD-Maps) improve the safety and comfort of highly automated vehicles. Such maps are lane-accurate down to the centimeter level. However, the road network infrastructure is subject to constant changes (e.g. through constructions works, accidents, ...). This requires frequent and fast map updates to be provided to the vehicles. In this paper we propose a road hazard detection algorithm that identifies and marks the extent of such changes based on GNSS data crowdsourced by appropriately equipped vehicles. To increase the detection speed, we integrate smartphones as cheap and ubiquitous devices into the collection process. To deal with the limited accuracy of collected data w.r.t. lane accurate curvatures of a street, we enhance existing algorithmic clustering approaches by leveraging additional meta-data such as the quality of the collected GNSS points and the vehicle’s current lane position, relying solely on sensory equipment built into today’s smartphones. Our concept is evaluated with real world measurements in a highway construction site scenario showing improved performance in comparison to the state of the art Kernel Density Estimation algorithm.|
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