I. Introduction
Recently, with increasing interests and needs for autonomous vehicles, many researches of the self-driving cars have been aiming for the level 4 and 5 in autonomous driving technology [21], [22], [24]. When it comes to beyond level 4 in autonomous driving technology, the vehicle should be able to deal with various kinds of situations around the self-driving vehicle in order to arrive at the targeted destination successfully. Thus, to accomplish its goal even under adverse weather conditions, the autonomous vehicle need to detect its surrounding situations and classify them to solve the threating features in the diverse driving environments. For the identification and classification of the threats, it is necessary to study on sensor blockages (e.g., rain, snow, dust, fog, and others), which are caused by direct contact on sensors or indirect effects on the sensors according to their properties [23], [24]. Since autonomous vehicles in the future should be robust enough against harsh weather conditions, it is necessary for the engineers to scientifically investigate what kinds of difficulties and effectiveness due to abnormal weather conditions with diverse sensors installed the autonomous vehicle are involved in recognizing properly the environmental situations [25]–[27].