Vehicle Localization using 76GHz Omnidirectional Millimeter-Wave Radar for Winter Automated Driving

This paper presents the 76GHz MWR (Millimeter-Wave Radar)-based self-localization method for automated driving during snowfall. Previously, there were many LIDAR (Light Detection and Ranging)-based localization techniques proposed for high measurement accuracy and robustness to changes of day and night. However, they did not provide effective approaches for snow conditions because of sensing noise (i.e., environmental resistance) created by snowfall. Therefore, this paper developed a MWR-based map generation and a real-time localization method by modeling the uncertainties of error propagation. Quantitative evaluations are performed on driving data with and without snow conditions, using a LIDAR-based method as the baseline. Experimental results show that a lateral root mean square error of about 0. 25m can be obtained, regardless of the presence or absence of snowfall. Thus, it can be investigated that a potential performance of radar-based localization.