This project proposes a cross-layer framework in which vehicular wireless networking and platoon control interact with each other to tame cyber-physical uncertainties. Based on the real-time capacity region of wireless networking and the physical process of vehicle movements, platoon control selects its control strategies and the corresponding requirements on the timeliness and throughput of wireless data delivery to optimize control performance. Based on the requirements from platoon control, wireless networking controls co-channel interference and adapts to cyber-physical uncertainties to ensure the timeliness and throughput of single-hop as well as multi-hop broadcast. For proactively addressing the impact of vehicle mobility on wireless broadcast, wireless networking also leverages input from platoon control on vehicle movement prediction. In realizing the cross-layer framework, wireless scheduling ensures agile, predictable interference control in the presence of cyber-physical uncertainties. If successful, this project will lead to a general and rigorous framework for wireless vehicular cyber-physical network control that will enable safe, efficient, and clean transportation. The principles and techniques for taming cyber-physical uncertainties will provide insight into other application domains of wireless networked sensing and control such as unmanned aerial vehicles and smart power grids. This project will also develop integrative research and education on wireless cyber-physical systems through multi-level, multi-component educational activities.

The focus of this project is the efficient implementation of multiple control and non-control automotive applications in a distributed embedded system (DES) with a goal of developing safe, dependable, and secure Automotive CPS. DES are highly attractive due to the fact that they radically enhance the capabilities of the underlying system by linking a range of devices and sensors and allowing information to be processed in unprecedented ways. Deploying control and non-control applications on a modern DES, which uses advanced processor and communication technology, introduces a host of challenges in their analysis and synthesis, and leads to a large semantic gap between models and their implementation. This gap will be filled via the development of a novel CPS architecture by stitching together common fundamental principles of multimodality from real-time systems and related notions of switching in control theory and integrating them into a co-design of real-time platforms and adaptive controllers. This architecture will be validated at the Toyota Technical Center in the context of engine control and diagnostics. The results of this project will provide the science and technology for a foundation in any and all infrastructure systems ranging from finance and energy to telecommunication and transportation where distributed embedded systems are present. In addition to training the graduate and undergraduate students, and mentoring a post-doctoral associate who will gain multi-domain expertise in advanced control, real-time computation and communication, and performance analysis, an inter-school graduate and an integrated summer course will be developed on control in embedded systems and combined with on-going outreach programs at MIT and UPenn for minority and women undergraduate students and K-12 students.

Effective response and adaptation to the physical world, and rigorous management of such behaviors through programmable computational means, are mandatory features of cyber physical systems (CPS). However, achieving such capabilities across diverse application requirements surpasses the current state of the art in system platforms and tools. Current computational platforms and tools often treat physical properties individually and in isolation from other cyber and physical attributes. They do not adequately support the expression, integration, and enforcement of system properties that span cyber and physical domains. This results in inefficient use of both cyber and physical resources, and in lower system effectiveness overall. This work investigates novel approaches to these important problems, based on modularizing and integrating diverse cyber-physical concerns that cross-cut physical, hardware, instruction set, kernel, library, and application abstractions. The three major thrusts of this research are 1) establishing foundational models for expressing, analyzing, enforcing, and measuring different conjoined cyber-physical properties, 2) conducting a fundamental re-examination of system development tools and platforms to identify how different application concerns that cut across them can be modularized as cyber-physical system aspects, and 3) developing prototype demonstrations of our results to evaluate further those advances in the state of the art in aspect-oriented techniques for CPS, to help assess the feasibility of broader application of the approach. The broader impact of this work will be through dissemination of academic papers, and open platforms and tools that afford unprecedented integration of cyber-physical properties.

The objective of this research is to develop methods for the operation and design of cyber physical systems in general, and energy efficient buildings in particular. The approach is to use an integrated framework: create models of complex systems from data; then design the associated sensing-communication-computation-control system; and finally create distributed estimation and control algorithms, along with execution platforms to implement these algorithms. A special emphasis is placed on adaptation. In particular, buildings and their environments change with time, as does the way in which buildings are used. The system must be designed to detect and respond to such changes. The proposed research brings together ideas from control theory, dynamical systems, stochastic processes, and embedded systems to address design and operation of complex cyber physical systems that were previously thought to be intractable. These approaches provide qualitative understanding of system behavior, algorithms for control, and their implementation in a networked execution platform. Insights gained by the application of model reduction and adaptation techniques will lead to significant developments in the underlying theory of modeling and control of complex systems. The research is expected to directly impact US industry through the development of integrated software-hardware solutions for smart buildings. Collaborations with United Technologies Research Center are planned to enhance this impact. The techniques developed are expected to apply to other complex cyber-physical systems with uncertain dynamics, such as the electric power grid. The project will enhance engineering education through the introduction of cross-disciplinary courses.

The objective of this research is to develop methods for the operation and design of cyber physical systems in general, and energy efficient buildings in particular. The approach is to use an integrated framework: create models of complex systems from data; then design the associated sensing-communication-computation-control system; and finally create distributed estimation and control algorithms, along with execution platforms to implement these algorithms. A special emphasis is placed on adaptation. In particular, buildings and their environments change with time, as does the way in which buildings are used. The system must be designed to detect and respond to such changes. The proposed research brings together ideas from control theory, dynamical systems, stochastic processes, and embedded systems to address design and operation of complex cyber physical systems that were previously thought to be intractable. These approaches provide qualitative understanding of system behavior, algorithms for control, and their implementation in a networked execution platform. Insights gained by the application of model reduction and adaptation techniques will lead to significant developments in the underlying theory of modeling and control of complex systems. The research is expected to directly impact US industry through the development of integrated software-hardware solutions for smart buildings. Collaborations with United Technologies Research Center are planned to enhance this impact. The techniques developed are expected to apply to other complex cyber-physical systems with uncertain dynamics, such as the electric power grid. The project will enhance engineering education through the introduction of cross-disciplinary courses.

The objective of this research is to develop a trustworthy and high-performance neural-machine interface (NMI) that accurately determines a user?s locomotion mode in real-time for neural-controlled artificial legs. The proposed approach is to design the NMI by integrating a new pattern recognition strategy with a high-performance computing embedded system. This project tackles the challenges of accurate interpretation of information from the neuromuscular system, a physical system, using appropriate computation in a cyber system to process the information in real-time. The neural-machine interface consists of multiple sensors that reliably monitor the neural and mechanical information and a set of new algorithms that can fuse and coordinate the highly dynamic information for accurate identification of user intent. The algorithm is to be implemented on a high-performance graphic processing unit (GPU) to meet real-time requirements. This project has the potential to enable the design of neural-controlled artificial legs and may initiate a new direction for research in and the design of prosthetic leg systems. Innovations in this domain have the potential to improve the quality of life of leg amputees, including soldiers with limb amputations. The proposed approaches seek to permit cyber systems to cope with physical uncertainty and dynamics, a common challenge in cyber-physical systems, and to pave a way for applying high-performance computing in biomedical engineering. Besides providing comprehensive training to undergraduate and graduate students, the investigators plan to introduce community college students to cyber-physical systems concepts in an interactive and engaging manner.

The objective of this inter-disciplinary research is to develop new technologies to transform the streets of a city into a hybrid transportation/communication system, called the Intelligent Road (iRoad), where autonomous wireless devices are co-located with traffic signals to form a wireless network that fuses real-time transportation data from all over the city to make a wide range of new applications possible. The approach is to build new capacities of quantitative bandwidth distribution, rate/delay assurance, and location-dependent security on a pervasive wireless platform through distributed queue management, adaptive rate control, and multi-layered trust. These new capacities lead to transformative changes in the way the transportation monitoring and control functions are designed and operated. Many technical challenges faced by the iRoad system are open problems. New theories/protocols developed in this project will support sophisticated bandwidth management, quality of service, multi-layered trust, and information fusion in a demanding environment where critical transportation functions are implemented. Solving these fundamental problems advances the state of the art in both wireless technologies and transportation engineering. The research outcome is likely to be broadly applicable in other wireless systems. The economic and societal impact of the iRoad system is tremendous at a time when the country is modernizing its ailing transportation infrastructure. It provides a pervasive communication infrastructure and engineering framework to build new applications such as real-time traffic map, online best-route query, intelligent fuel-efficient vehicles, etc. The research results will be disseminated through course materials, academic publication, industry connection, and presentations at the local transportation department.

The objective of this research is to develop truly intelligent, automated driving through a new paradigm that tightly integrates probabilistic perception and deterministic planning in a formal, verifiable framework. The interdisciplinary approach utilizes three interlinked tasks. Representations develops new techniques for constructing and maintaining representations of a dynamic environment to facilitate higher-level planning. Anticipation and Motion Planning develops methods to anticipate changes in the environment and use them as part of the planning process. Verifiable Task Planning develops theory and techniques for providing probabilistic guarantees for high-level behaviors. Ingrained in the approach is the synergy between theory and experiment using an in house, fully equipped vehicle. The recent Urban Challenge showed the current brittleness of autonomous driving, where small perception mistakes would propagate into planners, causing near misses and small accidents; Fundamentally, there is a mismatch between probabilistic perception and deterministic planning, leading to "reactive" rather than "intelligent" behaviors. The proposed research directly addresses this by developing a single, unified theory of perception and planning for intelligent cyber-physical systems. Near term, this research could be used to develop advanced safety systems in cars. The elderly and physically impaired would benefit from inexpensive, advanced automation in cars. Far term, the advanced intelligence could lead to automated vehicles for applications such as cooperative search and rescue. The research program will educate students through interdisciplinary courses in computer science and mechanical engineering, and experiential learning projects. Results will be disseminated to the community including under-represented colleges and universities.

The objective of this research is to investigate how to replace human decision-making with computational intelligence at a scale not possible before and in applications such as manufacturing, transportation, power-systems and bio-sensors. The approach is to build upon recent contributions in algorithmic motion planning, sensor networks and other fields so as to identify general solutions for planning and coordination in networks of cyber-physical systems. The intellectual merit of the project lies in defining a planning framework, which integrates simulation to utilize its predictive capabilities, and focuses on safety issues in real-time planning problems. The framework is extended to asynchronous coordination by utilizing distributed constraint optimization protocols and dealing with inconsistent state estimates among networked agents. Thus, the project addresses the frequent lack of well-behaved mathematical models for complex systems, the challenges of dynamic and partially-observable environments, and the difficulties in synchronizing and maintaining a unified, global world state estimate for multiple devices over a large-scale network. The broader impact involves the development and dissemination of new algorithms and open-source software. Research outcomes will be integrated to teaching efforts and undergraduate students will be involved in research. Underrepresented groups will be encouraged to participate, along with students from the Davidson Academy of Nevada, a free public high school for gifted students. At a societal level, this project will contribute towards achieving flexible manufacturing floors, automating the transportation infrastructure, autonomously delivering drugs to patients and mitigating cascading failures of the power network. Collaboration with domain experts will assist in realizing this impact.