A-WetDri is an adverse weather driving dataset designed to improve the robustness and generalization of autonomous driving perception models in adverse weather conditions. The dataset contains 42,390 samples, 19,344 of which are simulated data and 23,046 are real-world data. The dataset covers four environmental scenarios (rain, fog, night, snow, and clear weather) and various object categories (cars, trucks, bicycles, motorcycles, pedestrians, and traffic signs and lights).