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Found 7 papers, 0 papers with code
CLIPping the Limits: Finding the Sweet Spot for Relevant Images in Automated Driving Systems Perception Testing
Image data sets are therefore collected for the testing of automated driving systems, but it is non-trivial to find specific images in these data sets.
The Machine Vision Iceberg Explained: Advancing Dynamic Testing by Considering Holistic Environmental Relations
To illustrate this point, we draw an analogy to a ship navigating towards an iceberg to show potential hidden challenges in current MV testing strategies.
EfficientPPS: Part-aware Panoptic Segmentation of Transparent Objects for Robotic Manipulation
The use of autonomous robots for assistance tasks in hospitals has the potential to free up qualified staff and im-prove patient care.
Unveiling Objects with SOLA: An Annotation-Free Image Search on the Object Level for Automotive Data Sets
Huge image data sets are the fundament for the development of the perception of automated driving systems.
An Application of Scenario Exploration to Find New Scenarios for the Development and Testing of Automated Driving Systems in Urban Scenarios
Verification and validation are major challenges for developing automated driving systems.
A taxonomy for quality in simulation-based development and testing of automated driving systems
In this paper, we propose a taxonomy to serve a better understanding of the concept of quality in the development and testing process to have a clear separation and insight where further testing is needed -- both in terms of automated driving systems and simulation, including their simulation models and scenarios used for testing.
Software Engineering
SceML - A Graphical Modeling Framework for Scenario-based Testing of Autonomous Vehicles
Scenariobased testing is an approach to tackle this problem and reduce necessary test drives by replacing driven kilometers with simulations of relevant or interesting scenarios.
Autonomous Vehicles
Software Engineering
