Applications of CPS technologies used in the planning, functional design, operation and management of facilities for any mode of transportation in order to provide for the safe, efficient, rapid, comfortable, convenient, economical, and environmentally compatible movement of people and goods.
Recent progress in battery technology has made it possible to use batteries to power various physical platforms, such as ground/air/water vehicles. These platforms require hundreds/thousands of battery cells to meet their power and energy needs. Of these, automobiles, locomotives, and unmanned air vehicles (UAVs) face the most stringent environmental challenges. In particular, and of special importance to the automotive industry, is the transition from conventional powertrains to (plug-in) hybrid and electric vehicles, all of which are subject to environmental and operational variations.
Cyber-Physical Systems (CPS) that contain self-modifying smart components can improve and self-repair, but sometimes at the cost of impeding model-based Verification and Validation (V&V). In this work, we focus on maintaining short and long range V&V capability in a system containing self-adaptive smart components. In this work, we focus on smart component based in-flight control adaptation of damaged Flapping-Wing Micro Air Vehicles (FW-MAV).
Many safety-critical cyber-physical systems rely on advanced sensing capabilities to react to changing
environmental conditions. However, cost-effective deployments of such capabilities have remained
elusive. Such deployments will require software infrastructure that enables multiple sensor-processing
streams to be multiplexed onto a common hardware platform at reasonable cost, as well as tools and
methods for validating that required processing rates can be maintained.
Security and privacy concerns in the increasingly interconnected world are receiving much attention from the research community, policymakers, and general public. However, much of the recent and on-going efforts concentrate on privacy in communication and social interactions. The advent of cyber-physical systems, which aim at tight integration between distributed computational intelligence, communication networks, physical world, and human actors, opens new possibilities for developing intelligent systems with new capabilities.
The current lack of toolchain for high confidence testing, validation and verification of advanced, connected and automated/autonomous vehicles can impede and even entirely prevent the introduction of such vehicles into mass production. To address this challenge, this projects develops theory, methods, and tools for generating and optimizing test trajectories and data inputs that can maximize opportunities to uncover faults in both physical and cyber domain in future automotive vehicles.
Optimization algorithms used in a real-time and safety-critical context offer the potential for considerably advancing robotic and autonomous systems by improving their ability to execute complex missions. However, this promise cannot happen without proper attention to the considerably stronger operational constraints that real time, safety-critical applications must meet, unlike their non-real-time, desktop counterparts.
Cyber-physical processors work in harsh environments and often suffer very high operating temperatures. High temperatures accelerate processor aging and increase failure rate. Effective thermal-aware management is required to meet the computational demands of the application while reducing processor thermal stress.
This poster showcases progress on the NSF Knowledge-Aware Cyber-Physical Systems project. We have identified a case study to be used as a stepping stone in the study of Air France Flight 447, and have started using it to understand and show-case the features of the logic under development. It highlights the important distinction between observable and unobservable events, and has led to a better representation of pilot intuition while flying.
