Related papers: A Roadmap for Simulation-Based Testing of Autonomo…
Context: New software development patterns are emerging aiming at accelerating the process of delivering value. One is Continuous Experimentation, which allows to systematically deploy and run instrumented software variants during…
Cyber physical systems CPSs embodies the conception as well as the implementation of the integration of the state-of-art technologies in sensing, communication, computing, and control. Such systems incorporate new trends such as cloud…
The mass production of complex software has made it impossible to manually test it for security vulnerabilities. Automated security testing tools come in a variety of flavors, function at various stages of software development, and target…
Cyber-Physical Systems (CPS) integrate physical and embedded systems with information and communication technology systems, monitoring and controlling physical processes with minimal human intervention. The connection to information and…
Autonomous systems are highly complex and present unique challenges for the application of formal methods. Autonomous systems act without human intervention, and are often embedded in a robotic system, so that they can interact with the…
Despite extensive research, the testing of autonomous driving systems (ADS) landscape remains fragmented, and there is currently no basis for an informed technical assessment of the importance and contribution of the current state of the…
Cyber-Physical Systems (CPSs) have become an intrinsic part of the 21st century world. Systems like Smart Grids, Transportation, and Healthcare help us run our lives and businesses smoothly, successfully and safely. Since malfunctions in…
Edge computing is projected to have profound implications in the coming decades, proposed to provide solutions for applications such as augmented reality, predictive functionalities, and collaborative Cyber-Physical Systems (CPS). For such…
Cyber-physical systems (CPS), in most instances, represent systems of systems with an informationally decentralized structure such as emerging mobility systems, networked control systems, sustainable manufacturing, smart power grids, power…
Autonomous driving has gained significant advancements in recent years. However, obtaining a robust control policy for driving remains challenging as it requires training data from a variety of scenarios, including rare situations (e.g.,…
In an increasingly interconnected world, Cyber-Physical Systems (CPS) are essential to critical industries like healthcare, transportation, and manufacturing, merging physical processes with computational intelligence. However, the security…
Virtualization of computing and networking, IT-OT convergence, cybersecurity and AI-based enhancement of autonomy are significantly increasing the complexity of CPS and CPSoS. New challenges have emerged to demonstrate that these systems…
In Industry 4.0, Cyber-Physical Systems (CPS) generate vast data sets that can be leveraged by Artificial Intelligence (AI) for applications including predictive maintenance and production planning. However, despite the demonstrated…
The rapidly evolving field of autonomous driving systems (ADSs) is full of promise. However, in order to fulfil these promises, ADSs need to be safe in all circumstances. This paper introduces ISS-Scenario, an autonomous driving testing…
Autonomous driving has made significant progress in both academia and industry, including performance improvements in perception task and the development of end-to-end autonomous driving systems. However, the safety and robustness…
The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by escalating system complexity, hardware-software heterogeneity, and the integration of…
The integration of artificial intelligence into automated penetration testing (AutoPT) has highlighted the necessity of simulation modeling for the training of intelligent agents, due to its cost-efficiency and swift feedback capabilities.…
Embodied AI systems, comprising AI models and physical plants, are increasingly prevalent across various applications. Due to the rarity of system failures, ensuring their safety in complex operating environments remains a major challenge,…
Simulating physical systems is a core component of scientific computing, encompassing a wide range of physical domains and applications. Recently, there has been a surge in data-driven methods to complement traditional numerical simulations…
As Autonomous Systems (AS) become more ubiquitous in society, more responsible for our safety and our interaction with them more frequent, it is essential that they are trustworthy. Assessing the trustworthiness of AS is a mandatory…