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Predicting the Influence of Rain on LIDAR in ADAS

Center for Advanced Vehicular Systems, Mississippi State University, Mississippi State, MS 39762, USA
Author to whom correspondence should be addressed.
Electronics 2019, 8(1), 89;
Received: 19 December 2018 / Revised: 9 January 2019 / Accepted: 10 January 2019 / Published: 15 January 2019
PDF [2024 KB, uploaded 15 January 2019]


While it is well known that rain may influence the performance of automotive LIDAR sensors commonly used in ADAS applications, there is a lack of quantitative analysis of this effect. In particular, there is very little published work on physically-based simulation of the influence of rain on terrestrial LIDAR performance. Additionally, there have been few quantitative studies on how rain-rate influences ADAS performance. In this work, we develop a mathematical model for the performance degradation of LIDAR as a function of rain-rate and incorporate this model into a simulation of an obstacle-detection system to show how it can be used to quantitatively predict the influence of rain on ADAS that use LIDAR. View Full-Text
Keywords: perception in challenging conditions; obstacle detection and classification; dynamic path-planning algorithms perception in challenging conditions; obstacle detection and classification; dynamic path-planning algorithms

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Goodin, C.; Carruth, D.; Doude, M.; Hudson, C. Predicting the Influence of Rain on LIDAR in ADAS. Electronics 2019, 8, 89.

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