Adverse weather conditions such as fog, heavy rain, snow, and wind can severely limit the functionality of sensors and cameras. Although the applications appear to work well in dry, sunny weather, those are just the best-case scenarios.
Mar 13, 2019 · Our simulation results show that the detection range of mm-wave radar can be reduced by up to 45% under severe rainfall conditions. Moreover, ...
Mar 8, 2020 · 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, ...
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One of the most critical issues in the development of autonomous vehicles and driver assistance systems is their poor performance under adverse weather ...
This article characterize the effect of rainfall on millimeter-wave (mmwave) radar, which considers both the rain attenuation and the backscatter effects, ...
The Impact of Adverse Weather Conditions on Autonomous Vehicles: Examining how rain, snow, fog and hail affect the performance of a self-driving car – PAVE.
Phenomena like fog, haze, sandstorms, and strong light severely decrease visibility and raise driving risks (Mehra et al., 2021). Secondary problems directly or ...
Dec 19, 2023 · The results indicated that as the intensity of fog and rain escalated, the performance of the LiDAR sensors correspondingly deteriorated.
Jan 8, 2021 · The car's sensors can be blocked by snow, ice or torrential downpours, and their ability to "read" road signs and markings can be impaired.
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May 2, 2023 · This paper analyzes the sensor signals of these three sensor technologies under rain and fog as well as day and night. A data set of a driving ...