Abstract
People use conventional maps for orientation in various environments. With the increase of traffic participant number, restrictions of conventional maps result in traffic congestion and an increased number of accidents. We could overcome such restrictions of conventional maps with High Definition (HD) maps. On top of conventional maps, HD maps provide detailed real-time information about traffic participants in monitored areas. Consequently, HD maps enable faster deployment of autonomous driving systems and provide significant improvement to Smart Cities. We can provide such additional real-time information as a result of an object detection algorithm. We propose a novel solution in developing an HD map layer by combining multiple object detection results. Traffic is monitored from multiple cameras observing vehicles and pedestrians from different points of view. We tested our solution on an urban environment, upgrading the public Geolocation map to an HD map.
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