The impact of adverse weather conditions on autonomous vehicles

how rain, snow, fog, and hail affect the performance of a self-driving car

Shizhe Zang, Ming Ding, David Smith, Paul Tyler, Thierry Rakotoarivelo, Mohamed Ali Kaafar

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)103-111
Number of pages9
JournalIEEE Vehicular Technology Magazine
Volume14
Issue number2
Early online date12 Mar 2019
DOIs
Publication statusPublished - Jun 2019

Keywords

  • Cameras
  • Global Positioning System
  • Laser radar
  • Rain
  • Sensors

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