# Examining the Optimization of Spray Cleaning Performance for LiDAR Sensor
## 4 Conclusions  
This study investigated the effects of various factors, including washer pressure, spray time, spray angle, and target point, on the cleaning optimization direction of LiDAR sensors for autonomous driving technologies.  
The results of this study suggest that washer pressure and spray time have the biggest impact on cleaning performance. However, the washer pressure cannot be infinitely increased due to physical limits and the cost of pumps. In this study, the effective water pressure was determined to be 7-8 bars based on the optimization results. Since spray time is related to the amount of water and more water is consumed with an increase in spray time, the washer reservoir tank capacity should be considered. Furthermore, the washer fluid obstructs the LiDAR sensor during spraying, and the resulting effect on sensor cleanliness may adversely affect the safety of autonomous driving operations. Accordingly, repeated spraying with short spray times (Table 8) was employed to ensure visibility even during washer operation. The highest cleaning rate was observed when the target point was positioned at approximately 10 mm. The optimal condition of the spray angle was observed to be between 20\({}^{\circ}\) and 30\({}^{\circ}\).  
A fan-shaped spray-type washer nozzle with a 60\({}^{\circ}\) spray angle, which is the most commonly used type of washer nozzle, was used in this study. In addition to the LiDAR window cover used in this study, various shapes can be created by adjusting the number of nozzles and applying them to window covers. The DOE was used to find the optimization direction while reducing a large number of experimentations, and the derived results were re-verified to secure the reliability of the optimization results. Detailed discussions on the experimental sample selection method, pretest, evaluation equipment, and analytical tools are expected to find applications to important materials selection by sensor cleaning-related manufacturers to develop technologies.  
Conceptualization, S.S.; methodology, S.S.; software, H.L.; validation, H.-C.R.; formal analysis, J.J.; investigation, S.B. and H.C.; data curation, H.L.; writing--original draft preparation, S.S.; writing--review and editing, J.L. ([PERSON]) and H.-C.R.; visualization, J.L. ([PERSON]) and W.L.; supervision, H.-C.R.; project administration, J.L. ([PERSON]). All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Project No. RS-2021_KA162419).  
Not applicable.  
The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding authors.  
We thank [PERSON] of SL Company for their generous technical support of this study and [PERSON] for proofreading the statistics and manuscript.  
[PERSON] and [PERSON] were employed by SL Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.  
**Figure A1. Sample photographs of experimental results for four standards.**