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While techniques have been developed for chance constrained stochastic optimal control using sample disturbance data that provide a probabilistic confidence bound for chance constraint satisfaction, far less is known about how to use sample…
Accident detection using Closed Circuit Television (CCTV) footage is one of the most imperative features for enhancing transport safety and efficient traffic control. To this end, this research addresses the issues of supervised monitoring…
The widescale deployment of Autonomous Vehicles (AV) seems to be imminent despite many safety challenges that are yet to be resolved. It is well known that there are no universally agreed Verification and Validation (VV) methodologies to…
In this paper, we introduce Context-Aware Priority Sampling (CAPS), a novel method designed to enhance data efficiency in learning-based autonomous driving systems. CAPS addresses the challenge of imbalanced datasets in imitation learning…
Modern vehicles are complex cyber-physical systems made of hundreds of electronic control units (ECUs) that communicate over controller area networks (CANs). This inherited complexity has expanded the CAN attack surface which is vulnerable…
Control applications for cyber-physical systems must make reliably safe control decisions in the presence of continuous dynamics as well as stochastic uncertainty. Providing safety guarantees for such systems requires formal modeling and…
As the autonomous vehicle industry continues to grow, various companies are exploring the use of aftermarket kits to retrofit existing vehicles with semi-autonomous capabilities. However, differences in implementation of the controller area…
Connected and automated vehicles (CAVs) rely on wireless communication to exchange state information for distributed control, making communication delays a critical factor that can affect vehicle motion and degrade control performance,…
Learning-based model predictive control has been widely applied in autonomous racing to improve the closed-loop behaviour of vehicles in a data-driven manner. When environmental conditions change, e.g., due to rain, often only the…
Emerging vehicle automation and communication systems (VACS) may contribute to the improvement of vehicle travel time and the mitigation of motorway traffic congestion on the basis of appropriate control strategies. This work considers the…
Predictive maintenance plays a critical role in ensuring the uninterrupted operation of industrial systems and mitigating the potential risks associated with system failures. This study focuses on sensor-based condition monitoring and…
Running Convolutional Neural Network (CNN) based applications on edge devices near the source of data can meet the latency and privacy challenges. However due to their reduced computing resources and their energy constraints, these edge…
Modern vehicles contain a few controller area networks (CANs), which allow scores of on-board electronic control units (ECUs) to communicate messages critical to vehicle functions and driver safety. CAN provide a lightweight and reliable…
Vehicular Controller Area Networks (CANs) are susceptible to cyber attacks of different levels of sophistication. Fabrication attacks are the easiest to administer -- an adversary simply sends (extra) frames on a CAN -- but also the easiest…
The rigorous safety verification of control systems in critical applications is essential, given their increasing complexity and integration into everyday life. Simulation-based falsification approaches play a pivotal role in the safety…
Atomistic simulations provide valuable insights into the physical processes governing material behavior. However, their applicability is fundamentally constrained by the limited time scales accessible to brute-force simulations. This…
We propose and experimentally evaluate a novel method that dynamically changes the contention window of access points based on system load to improve performance in a dense Wi-Fi deployment. A key feature is that no MAC protocol changes,…
Reinforcement Learning (RL) has demonstrated state-of-the-art results in a number of autonomous system applications, however many of the underlying algorithms rely on black-box predictions. This results in poor explainability of the…
Controller Area Network (CAN) is one of the in-vehicle network protocols that is used to communicate among Electronic Control Units (ECUs) and has been de-facto standard. CAN is simple and has several vulnerabilities such as unable to…
In this work, we face the issue of achieving an efficient dynamic mapping in vehicular networking scenarios, i.e., to obtain an accurate estimate of the positions and trajectories of connected vehicles in a certain area. State of the art…