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Found 10 papers, 0 papers with code
Towards Scenario- and Capability-Driven Dataset Development and Evaluation: An Approach in the Context of Mapless Automated Driving
The foundational role of datasets in defining the capabilities of deep learning models has led to their rapid proliferation.
A Prototypical Expert-Driven Approach Towards Capability-Based Monitoring of Automated Driving Systems
Using the online monitor, we infer the quality of the system's capabilities based on technical measurements acquired at runtime.
Identifikation auslösender Umstände von SOTIF-Gefährdungen durch systemtheoretische Prozessanalyse
Developers have to obtain a sound understanding of existing risk potentials already in the concept phase of driverless vehicles.
On Assumptions with Respect to Occlusions in Urban Environments for Automated Vehicle Speed Decisions
Automated driving systems are subject to various kinds of uncertainty during design, development, and operation.
Risk Management Core -- Towards an Explicit Representation of Risk in Automated Driving
While current automotive safety standards provide implicit guidance on how unreasonable risk can be avoided, manufacturers are required to specify risk acceptance criteria for Automated Driving Systems (SAE Level 3 and higher).
ODD-Centric Contextual Sensitivity Analysis Applied To A Non-Linear Vehicle Dynamics Model
Hence, the quality of the underlying models has to be evaluated with respect to the ODD.
Ein Beitrag zur durchgängigen, formalen Verhaltensspezifikation automatisierter Straßenfahrzeuge
With the introduction of the \textit{semantic norm behavior analysis} a method is proposed, which contributes to a traceable mapping of concerns towards the behavior of an automated vehicle in its operational environment to a formal rule system of semantic concepts for considered scenarios.
Sensitivity Analysis for Vehicle Dynamics Models -- An Approach to Model Quality Assessment for Automated Vehicles
Model-based approaches have become increasingly popular in the domain of automated driving.
Systems and Control Systems and Control
Assessment of Deep Convolutional Neural Networks for Road Surface Classification
When parameterizing vehicle control algorithms for stability or trajectory control, the road-tire friction coefficient is an essential model parameter when it comes to control performance.
Towards a Functional System Architecture for Automated Vehicles
This paper presents a functional system architecture for an automated vehicle.
Systems and Control Robotics
