Adverse weather conditions are very challenging for autonomous driving because most of
the state-of-the-art sensors stop working reliably under these conditions. In order to develop …

Object detection is recognized as one of the most critical research areas for the perception of
self-driving cars. Current vision systems combine visible imaging, LIDAR, and/or RADAR …

In an increasing number of cars, the driver is supported by Advanced Driver Assistance
Systems (ADAS). In particular camera based ADAS are a key component for further …

Autonomous driving at level five does not only means self-driving in the sunshine. Adverse
weather is especially critical because fog, rain, and snow degrade the perception of the …

The vehicle's perception sensors radar, lidar and camera, which must work continuously and
without restriction, especially with regard to automated/autonomous driving, can lose …

Recently, self-driving vehicles have been introduced with several automated features
including lane-keep assistance, queuing assistance in traffic-jam, parking assistance and …

Autonomous Vehicle (AV) technologies are faced with several challenges under adverse
weather conditions such as snow, fog, rain, sun glare, etc. Object detection under adverse …

Compared to daytime, a larger proportion of accident happens during nighttime. The altered
visibility of the road scene for the drivers may partially explain this situation. The latter …

Adverse weather conditions such as fog, haze, snow, mist and glare create visibility
problems for applications of autonomous vehicles. To ensure safe and smooth operations in …

Introduction to Rain and Fog Attenuation on Automotive Surround Sensors Page 1
Introduction to Rain and Fog Attenuation on Automotive Surround Sensors Sinan …