Survey on scenario-based safety assessment of automated vehicles
S Riedmaier, T Ponn, D Ludwig, B Schick… - IEEE …, 2020 - ieeexplore.ieee.org
When will automated vehicles come onto the market? This question has puzzled the
automotive industry and society for years. The technology and its implementation have …
automotive industry and society for years. The technology and its implementation have …
Verisig: verifying safety properties of hybrid systems with neural network controllers
This paper presents Verisig, a hybrid system approach to verifying safety properties of
closed-loop systems using neural networks as controllers. We focus on sigmoid-based …
closed-loop systems using neural networks as controllers. We focus on sigmoid-based …
Testing deep neural networks
Deep neural networks (DNNs) have a wide range of applications, and software employing
them must be thoroughly tested, especially in safety-critical domains. However, traditional …
them must be thoroughly tested, especially in safety-critical domains. However, traditional …
Safety assurance of artificial intelligence-based systems: A systematic literature review on the state of the art and guidelines for future work
AVS Neto, JB Camargo, JR Almeida… - IEEE Access, 2022 - ieeexplore.ieee.org
The objective of this research is to present the state of the art of the safety assurance of
Artificial Intelligence (AI)-based systems and guidelines on future correlated work. For this …
Artificial Intelligence (AI)-based systems and guidelines on future correlated work. For this …
Formal verification of neural network controlled autonomous systems
In this paper, we consider the problem of formally verifying the safety of an autonomous
robot equipped with a Neural Network (NN) controller that processes LiDAR images to …
robot equipped with a Neural Network (NN) controller that processes LiDAR images to …
Structural test coverage criteria for deep neural networks
Deep neural networks (DNNs) have a wide range of applications, and software employing
them must be thoroughly tested, especially in safety-critical domains. However, traditional …
them must be thoroughly tested, especially in safety-critical domains. However, traditional …
Specification-based autonomous driving system testing
Autonomous vehicle (AV) systems must be comprehensively tested and evaluated before
they can be deployed. High-fidelity simulators such as CARLA or LGSVL allow this to be …
they can be deployed. High-fidelity simulators such as CARLA or LGSVL allow this to be …
Verification for machine learning, autonomy, and neural networks survey
This survey presents an overview of verification techniques for autonomous systems, with a
focus on safety-critical autonomous cyber-physical systems (CPS) and subcomponents …
focus on safety-critical autonomous cyber-physical systems (CPS) and subcomponents …
Learning safe neural network controllers with barrier certificates
We provide a new approach to synthesize controllers for nonlinear continuous dynamical
systems with control against safety properties. The controllers are based on neural networks …
systems with control against safety properties. The controllers are based on neural networks …
Training neural network controllers using control barrier functions in the presence of disturbances
S Yaghoubi, G Fainekos… - 2020 IEEE 23rd …, 2020 - ieeexplore.ieee.org
Control Barrier Functions (CBF) have been recently utilized in the design of provably safe
feedback control laws for nonlinear systems. These feedback control methods typically …
feedback control laws for nonlinear systems. These feedback control methods typically …