Perception and sensing for autonomous vehicles under adverse weather conditions: A survey
Abstract Automated Driving Systems (ADS) open up a new domain for the automotive
industry and offer new possibilities for future transportation with higher efficiency and …
industry and offer new possibilities for future transportation with higher efficiency and …
Seeing through fog without seeing fog: Deep multimodal sensor fusion in unseen adverse weather
The fusion of multimodal sensor streams, such as camera, lidar, and radar measurements,
plays a critical role in object detection for autonomous vehicles, which base their decision …
plays a critical role in object detection for autonomous vehicles, which base their decision …
Robust multimodal vehicle detection in foggy weather using complementary lidar and radar signals
Vehicle detection with visual sensors like lidar and camera is one of the critical functions
enabling autonomous driving. While they generate fine-grained point clouds or high …
enabling autonomous driving. While they generate fine-grained point clouds or high …
Guided curriculum model adaptation and uncertainty-aware evaluation for semantic nighttime image segmentation
Most progress in semantic segmentation reports on daytime images taken under favorable
illumination conditions. We instead address the problem of semantic segmentation of …
illumination conditions. We instead address the problem of semantic segmentation of …
A benchmark for lidar sensors in fog: Is detection breaking down?
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 …
weather is especially critical because fog, rain, and snow degrade the perception of the …
Map-guided curriculum domain adaptation and uncertainty-aware evaluation for semantic nighttime image segmentation
We address the problem of semantic nighttime image segmentation and improve the state-of-
the-art, by adapting daytime models to nighttime without using nighttime annotations …
the-art, by adapting daytime models to nighttime without using nighttime annotations …
CDAda: A curriculum domain adaptation for nighttime semantic segmentation
Autonomous driving needs to ensure all-weather safety, especially in unfavorable
environments such as night and rain. However, the current daytime-trained semantic …
environments such as night and rain. However, the current daytime-trained semantic …
Cooperative automated driving use cases for 5G V2X communication
Cooperative Automated Driving (CAD) brings together driving automation technology with
vehicle-to-X (V2X) communication in order to enable vehicles to coordinate their driving …
vehicle-to-X (V2X) communication in order to enable vehicles to coordinate their driving …
Artificial Intelligence-Assisted Robustness of Optoelectronics for Automated Driving: A Review
EJC Nacpil, J Han, I Jeon - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
Optoelectronic sensing systems are used in automated vehicles for in-cabin features such
as driver attention and distraction monitoring. As automated driving technology continues to …
as driver attention and distraction monitoring. As automated driving technology continues to …
Multi-weather city: Adverse weather stacking for autonomous driving
Autonomous vehicles make use of sensors to perceive the world around them, with heavy
reliance on vision-based sensors such as RGB cameras. Unfortunately, since these sensors …
reliance on vision-based sensors such as RGB cameras. Unfortunately, since these sensors …