8 citations · 16 across the 13 of their papers we have counts for
5 papers · 2 filters
Criticality Metrics for Relevance Classification in Safety Evaluation of Object Detection in Automated Driving
Jörg Gamerdinger, Sven Teufel, Stephan Amann +1
Ensuring safety is the primary objective of automated driving, which necessitates a comprehensive and accurate perception of the environment. While numerous performance evaluation…
SnowyLane: Robust Lane Detection on Snow-covered Rural Roads Using Infrastructural Elements
Jörg Gamerdinger, Benedict Wetzel, Patrick Schulz +2
Lane detection for autonomous driving in snow-covered environments remains a major challenge due to the frequent absence or occlusion of lane markings. In this paper, we present a…
DenoiseCP-Net: Efficient Collective Perception in Adverse Weather via Joint LiDAR-Based 3D Object Detection and Denoising
Sven Teufel, Dominique Mayer, Jörg Gamerdinger +1
While automated vehicles hold the potential to significantly reduce traffic accidents, their perception systems remain vulnerable to sensor degradation caused by adverse weather an…
S2S-Net: Addressing the Domain Gap of Heterogeneous Sensor Systems in LiDAR-Based Collective Perception
Sven Teufel, Jörg Gamerdinger, Oliver Bringmann
Collective Perception (CP) has emerged as a promising approach to overcome the limitations of individual perception in the context of autonomous driving. Various approaches have be…
Datasets for Lane Detection in Autonomous Driving: A Comprehensive Review
Jörg Gamerdinger, Sven Teufel, Oliver Bringmann
Accurate lane detection is essential for automated driving, enabling safe and reliable vehicle navigation across a variety of road scenarios. Numerous datasets have been introduced…