  Perception plays an important role in reliable decision-making for autonomous
vehicles. Over the last ten years, huge advances have been made in the field of
perception. However, perception in extreme weather conditions is still a
difficult problem, especially in rainy weather conditions. In order to improve
the detection effect of road targets in rainy environments, we analyze the
physical characteristics of the rain layer and propose a deraining
convolutional neural network structure. Based on this network structure, we
design an ablation experiment and experiment results show that our method can
effectively improve the accuracy of object detection in rainy conditions.
