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In this paper we present a series of road scene images recorded with a prototype high resolution low-THz imaging radar. The aim of this study is to assess the images in order to identify and extract features of interest for scene characterisation to aid the development of future autonomous vehicles. Images were recorded at multiple radar heights in order to assess the effect of illumination angle...
One of the most fundamental tasks in autonomous driving is the recognition of the road ahead. Using radar data, this is usually done via rule based algorithms. This paper proposes a deep learning approach to estimate the course of the ego lane based on occupancy grids generated by radar sensors. The method is also able to simultaneously give a reliability measurement of the predicted driving path...
We have recently presented a processor for traffic monitoring applications that combines the post-Doppler space-time adaptive processing (PD STAP) with a road map obtained from the freely available OpenStreetMap (OSM). In this paper, the positioning error model of this processor is presented and discussed. In fact, two error models are combined: one for the PD STAP detections and one for the OSM road...
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