Optimization of Dust Spray Parameters for Simulated LiDAR Sensor Contamination in Autonomous Vehicles Using a Face-Centered Composite Design

Light detection and ranging (LiDAR) provides three-dimensional environmental information that is critical for maintaining the safety and reliability of autonomous driving systems. However, dust accumulation on the LiDAR window can cause detection errors and degrade performance. This study determined the optimal spray conditions for accumulating dust to evaluate LiDAR sensor cleaning performance. A primary optimization experiment using spray pressure, spray speed, spray distance, and the number of sprays as variables showed that spray pressure and number of sprays had the most significant influence on the kinetic energy and distribution of dust particles. Notably, the interaction between spray distance and number of sprays—related to curvature effects—was identified as a key variable increasing process sensitivity. A supplementary experiment, which added spray angle as a variable, indicated that while spray pressure remained the most significant factor, spray angle and number of sprays had an indirect influence through interaction terms. Both experiments used the same response variable (point cloud data) interactions to stepwise analyze particle transfer and spatial diffusion. The resulting optimal conditions offer a standard basis for evaluating LiDAR cleaning performance and may help improve cleaning efficiency and maintenance strategies.