Predicting the Influence of Rain on LIDAR in ADAS

By Christopher T. Goodin, Daniel W. Carruth, Matthew Doude, Christopher R. Hudson. Electronics, 2019

204 citations recorded by the source corpus.

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.

Subfields: Automotive Engineering, Environmental Engineering, Instrumentation

View Paper: https://www.semanticscholar.org/paper/1a468965d9fb4db1047ef330d6bde49c9d476ecb

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In Automotive Engineering

1. Yu Wu
2. Qingqing Niu
3. Zhangjing Wang

Citations in the corpus

• Multi-Sensor Fusion in Automated Driving: A Survey (2020, methodology): “Reference [73] analyzed the influence of rainfall on LiDAR, and the results are shown in Fig.”