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◆ Sensors (Basel, Switzerland)2026-09-05

Impact of UK Weather on Autonomous Vehicle Radar, LiDAR and Camera Vision Systems.

Jessica Smith, Richard Dudley, David Jones, David Cheadle, Imran Mohamed, Fengping Li, Daniel Bownds, Hsun Yang, Joel Rapley, Andre Burgess, Mira Naftaly, Mayokun Aikomo, Jeremy Price, Nawal Husnoo, Stephan Havemann, Matthew Fry, Martin Osborne, James McGregor, Alan Vance

原始摘要(英文原文)· Original abstract
Measurements are presented from a purpose-built outdoor test facility for the assurance of situational awareness sensors for Autonomous Vehicles (AVs). The testbed included meteorological instrumentation for an accurate high-resolution picture of weather traversing the site. Static targets at ranges up to 250 m were observed simultaneously with multiple radar, LiDAR and camera systems exposed to the natural weather events over a two-year period. The aim of the testbed was to collect data over a prolonged period of time to ensure the maximum amount of variation in weather was encountered. Uniquely, the testbed treats the measurement of weather as an equal metrology challenge to that of measuring the CAV sensor response with the aim of understanding the extent to which it is possible to quantitatively correlate sensor performance degradation with weather parameters. In this paper case study examples of the testbed data for rainfall, fog and 'ideal' neutral conditions have been analysed. Correlations between sensor performance degradation and weather parameters were observed in several cases, including comparisons with rain rate and MOR (visibility). However, large uncertainties and complex interactions between weather-related performance reduction and secondary weather effects, like sensor window and target surface wetting, make an explicit determination of the severity at which a weather condition causes a sensor to become untrustworthy, problematic.
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Impact of UK Weather on Autonomous Vehicle Radar, LiDAR and Camera Vision Systems. — 科研速览 Science Skim