The Impact of Adverse Weather Conditions on Autonomous Vehicles: How Rain, Snow, Fog, and Hail Affect the Performance of a Self-Driving Car

By Shizhe Zang, Ming Ding, David B. Smith, P. Tyler, T. Rakotoarivelo, Mohamed Ali Kâafar. IEEE Vehicular Technology Magazine, 2019

395 citations recorded by the source corpus.

Recently, the development of autonomous vehicles and intelligent driver assistance systems has drawn a significant amount of attention from the general public. One of the most critical issues in the development of autonomous vehicles and driver assistance systems is their poor performance under adverse weather conditions, such as rain, snow, fog, and hail. However, no current study provides a systematic and unified review of the effect that weather has on the various types of sensors used in autonomous vehicles. In this article, we first present a literature review about the impact of adverse weather conditions on state-ofthe-art sensors, such as lidar, GPS, camera, and radar. Then, we characterize the effect of rainfall on millimeter-wave (mmwave) radar, which considers both the rain attenuation and the backscatter effects. Our simulation results show that the detection range of mm-wave radar can be reduced by up to 45% under severe rainfall conditions. Moreover, the rain backscatter effect is significantly different for targets with different radar cross-section (RCS) areas.

Subfields: Aerospace Engineering, Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/de749a9d7dca831238471a773e8786aa51757c06

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In Aerospace Engineering

1. Baofu Wu
2. Alexander Carballo
3. Sidi Lu
4. Ren Zhong
5. Qingyan Zhang
6. Yongtao Yao
7. Weisong Shi
8. Liangkai Liu

Citations in the corpus

• An Overview of Autonomous Vehicles Sensors and Their Vulnerability to Weather Conditions (2021, neutral): “Reference [37] examines a camera’s ability within a fog chamber of 2 micron and 6 micron size fog particles.”
• Computing Systems for Autonomous Driving: State of the Art and Challenges (2020, background): “The work of [222] characterized the effect of rainfall on millimeter-wave (mm-wave) radar and proved that under heavy rainfall conditions, the detection range of the millimeter-wave radar can be reduced by as much as 45%.”
• Perception and sensing for autonomous vehicles under adverse weather conditions: A survey (2021, methodology): “[18], the rain attenuation and back-scatter effects to mm-wave radar and the receiver noise were mathematically analyzed.”