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Son S, Lee W, Jung H, Lee J, Kim C, Lee H, Cho S, Jang J, Lee M, Ryu HC. Experimental Analysis of Various Blockage Performance for LiDAR Sensor Cleaning Evaluation. Sensors (Basel) 2023; 23:2752. [PMID: 36904952 PMCID: PMC10007043 DOI: 10.3390/s23052752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 02/25/2023] [Accepted: 02/28/2023] [Indexed: 06/18/2023]
Abstract
Autonomous driving includes recognition, judgment, and control technologies, and is implemented using sensors such as cameras, LiDAR, and radar. However, recognition sensors are exposed to the outside environment and their performance may deteriorate because of the presence of substances that interfere with vision, such as dust, bird droppings, and insects, during operation. Research on sensor cleaning technology to solve this performance degradation has been limited. This study used various types and concentrations of blockage and dryness to demonstrate approaches to the evaluation of cleaning rates for selected conditions that afford satisfactory results. To determine the effectiveness of washing, the study used the following criteria: washer, 0.5 bar/s and air, 2 bar/s, with 3.5 g being used three times to test the LiDAR window. The study found that blockage, concentration, and dryness are the most important factors, and in that order. Additionally, the study compared new forms of blockage, such as those caused by dust, bird droppings, and insects, with standard dust that was used as a control to evaluate the performance of the new blockage types. The results of this study can be used to conduct various sensor cleaning tests and ensure their reliability and economic feasibility.
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Affiliation(s)
- SungHo Son
- Department of Future Vehicle Research, Korea Automobile Testing and Research Institute, Hwaseong 18247, Republic of Korea
- Department of Convergence Science, University of Sahmyook, Seoul 01795, Republic of Korea
| | - WoongSu Lee
- Department of Future Vehicle Research, Korea Automobile Testing and Research Institute, Hwaseong 18247, Republic of Korea
| | - HyunGi Jung
- Department of Future Vehicle Research, Korea Automobile Testing and Research Institute, Hwaseong 18247, Republic of Korea
| | - JungKi Lee
- Department of Future Vehicle Research, Korea Automobile Testing and Research Institute, Hwaseong 18247, Republic of Korea
| | - ChaRyung Kim
- Department of Future Vehicle Research, Korea Automobile Testing and Research Institute, Hwaseong 18247, Republic of Korea
| | - HyunWoo Lee
- Department of Future Vehicle Research, Korea Automobile Testing and Research Institute, Hwaseong 18247, Republic of Korea
| | - SeoungWoo Cho
- Department of Future Vehicle Research, Korea Automobile Testing and Research Institute, Hwaseong 18247, Republic of Korea
| | - JeongAh Jang
- TOD Based Transportation Research Center, University of Ajou, Suwon 16499, Republic of Korea
| | - Michael Lee
- Department of Business Intelligence and Analytics, Legacy.com, 230 W Monroe Ste 400, Chicago, IL 60606, USA
| | - Han-Cheol Ryu
- Department of Convergence Science, University of Sahmyook, Seoul 01795, Republic of Korea
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