Vision Improvement in Automated Cars by Image Deraining

Gangula, Lokesh babu; Srikanth, Ganta; Cheggoju, Naveen; Satpute, V. R.

doi:10.1109/sceecs.2018.8546979

Cited by 1 publication

(1 citation statement)

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“…Besides, the authors propose the need for post-processing methods to mitigate the impact of rain and fog. For instance, a de-watering approach to enhance vision efficiency in rainfall is presented in [ 167 ]. We can hardly find studies which show the influence of snow and its interaction with the camera, due to the lack of snow-based simulators.…”

Section: Sensorsmentioning

confidence: 99%

The Perception System of Intelligent Ground Vehicles in All Weather Conditions: A Systematic Literature Review

Mohammed

Amamou

Ayevide

et al. 2020

Sensors

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Perception is a vital part of driving. Every year, the loss in visibility due to snow, fog, and rain causes serious accidents worldwide. Therefore, it is important to be aware of the impact of weather conditions on perception performance while driving on highways and urban traffic in all weather conditions. The goal of this paper is to provide a survey of sensing technologies used to detect the surrounding environment and obstacles during driving maneuvers in different weather conditions. Firstly, some important historical milestones are presented. Secondly, the state-of-the-art automated driving applications (adaptive cruise control, pedestrian collision avoidance, etc.) are introduced with a focus on all-weather activity. Thirdly, the most involved sensor technologies (radar, lidar, ultrasonic, camera, and far-infrared) employed by automated driving applications are studied. Furthermore, the difference between the current and expected states of performance is determined by the use of spider charts. As a result, a fusion perspective is proposed that can fill gaps and increase the robustness of the perception system.

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Section: Sensorsmentioning

confidence: 99%