Automotive LiDAR pollution detection system based on total internal reflection techniques

Manuel Trierweiler; Tobias Peterseim; Cornelius Neumann

doi:10.1117/12.2538416

25 February 2020 Automotive LiDAR pollution detection system based on total internal reflection techniques

Manuel Trierweiler, Tobias Peterseim, Cornelius Neumann

Proceedings Volume 11302, Light-Emitting Devices, Materials, and Applications XXIV; 1130216 (2020) https://doi.org/10.1117/12.2538416
Event: SPIE OPTO, 2020, San Francisco, California, United States

Abstract

In harsh weather conditions contaminants like water or particles from road dirt attach on the outer surfaces of a vehicle. This applies to the sensor systems of the vehicle as well, which is why they are separated from the environment with a protection window. In today's vehicles, a rain sensor can control the windshield wiper to ensure a clear view for the driver through the windshield. This technique can be applied to automotive light detection and ranging (LiDAR) sensors, which are particularly sensitive to contaminants. However, if solid particles attach on the protection window, the wiper cannot clean the surface properly until a cleaning solution is sprayed on the surface before. We present a method for detecting contaminants on this protection window using total internal reflection techniques. The proposed system is able to separate between liquid and solid contaminants, making the automatic control of a cleaning system consisting of a wiper and nozzles possible. Furthermore, the system yields a degree of contamination on the entire surface of the sensor cover which is of high importance for the data interpretation of the underlying LiDAR system.

Citation Download Citation

Manuel Trierweiler, Tobias Peterseim, and Cornelius Neumann "Automotive LiDAR pollution detection system based on total internal reflection techniques", Proc. SPIE 11302, Light-Emitting Devices, Materials, and Applications XXIV, 1130216 (25 February 2020); https://doi.org/10.1117/12.2538416

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available