Hybrid autonomous systems are those where groups of people are in direct, ongoing interaction with groups of autonomous robots or autonomous software. One prominent current example involves rush-hour traffic made up of a mixture of cars driven by people and cars driven by smart algorithms. However, emerging technologies in robotics, AI and ICT mean that hybrid autonomous systems of this kind will become increasingly common in a much wider set of situations: Emerging technologies in robotics, AI and ICT mean that hybrid autonomous systems of this kind will become increasingly common in a much wider set of situations: - a mixture of autonomous and human-operated drones making deliveries or monitoring public spaces; - a mixture of human traders and autonomous trading agents buying and selling stocks; - a mixture of autonomous and human-operated trains and trams providing efficient, integrated public transport; - autonomous systems assisting with search and rescue missions in disaster areas that are difficult or dangerous to access; - robot carers assisting care workers with the provision of social care in the home In each of these cases smooth, reliable, safe interaction amongst machines and people will be key to success. But how can we guarantee that self-driving cars won't cause a crash or gridlock? How can we understand how autonomous systems will respond to new situations (both acute shocks and long-term gradual changes in their environment), or changes in the way that people interact with them? Consequently, as we enter this new design space, a crucial challenge for the engineers of hybrid autonomous systems across all of these settings is ensuring that the system behaviour is Robust and Resilient and that it meets Regulatory demands: the R3 Challenge. T-B PHASE directly addresses this R3 Challenge for Hybrid Autonomous Systems Engineering, by bringing together expertise in robotics, AI, and systems engineering at the University of Bristol and Thales in a five-year project that targets fundamental autonomous system design problems in the context of three real-world Thales use cases: Hybrid Low-Level Flight, Hybrid Rail Systems, and Hybrid Search & Rescue. Bristol and Thales have a long-standing track record of research collaboration, and by jointly pursuing fundamental research questions in the context of highly practical design problems, alongside a programme of engagement with industry, the public and regulatory bodies, T-B PHASE will significantly advance our capability to operate confidently in one of the most important emerging areas for modern engineering.

RISC-V is an Instruction Set Architecture (ISA) design. An ISA is essentially a specification for the instructions any compatible processor implementation should be able to execute, and the resources those instructions can access; it acts as the interface between the processor implementation (hardware) and programs that execute on it (software). In sharp contrast with proprietary analogues such as the x86 ISA from Intel, RISC-V is an open source design. This means it can be used freely by anyone for any purpose, which, in part, has meant rapid development of a rich support infrastructure around the project: this includes a) vibrant developer and user communities, built around an associated non-profit foundation, b) numerous implementations of the ISA, both in HDL (i.e., a soft core for use on an FPGA platform) and silicon (i.e., physical ICs), and c) ports of programming tool-chains (e.g., GCC and LLVM) and operating systems (e.g., Linux). Similar openness is a core principle in security-critical contexts, contrasting with the alternative often colloquially termed "security by obscurity". This is particularly true in the field of cryptography, a technology routinely tasked with ensuring secrecy, robustness and provenience of our data (communicated or stored), and the authenticity of parties we interact with: open development of cryptographic standards, designs, and implementations is the modern norm. As a result, RISC-V presents various opportunities when used to execute cryptographic software. The proposed research goals capitalise on these opportunities, in a way designed to address advanced, persistent threats to our digital security, and, by extension, society. Specifically: 1) Since RISC-V can be implemented by anyone, it is possible to develop a core hardened against specific types of attack; the focus will be on the threat of side-channel attacks (which is particularly relevant to embedded use-cases, e.g., IoT). As well as doing so, the proposed research will investigation how detailed information about the implementation can be harnessed to produce more effective security evaluations. 2) Since RISC-V can be adapted by anyone, it is possible to develop various cryptography-specific extensions or variants of the ISA that offer either, for example, higher efficiency. If cryptographic software is more efficient it can also be more secure, because, for example, larger keys or more robust attack countermeasures can be deployed without as significant an impact on latency. 3) Evaluation of side-channel security can be prohibitive in the sense it needs various specific items of equipment. Harnessing a platform based on RISC-V, the proposed research with address this problem by offering a "lab. free" (i.e., cloud-based) acquisition and analysis workflow available to anyone.

Extensive work has been carried out on the technological, economic and societal potential for better management of energy demand. Huge potential of demand side management can only be exploited by exploring new ways to induce shifts of demand during peaks and hence reduce marginal costs. Digital communication technology can play a vital role in inducing this shift by enabling communication between the devices and the users. A holistic view of the interaction of all key-players - energy devices, energy supplier and energy users - is missing and this project aims at investigating this interaction using a multidisciplinary research team. The overall objective of this research is to evaluate the feasibility of using network technologies and sensor devices now being used in telecommunications, to create a Persuasive Energy-conscious Network (PEN) in a real life pilot setting and then study the potential impact on user behaviour leading to reductions in, and shifts in patterns of, loads of electricity. The project will aim to quantify the savings in carbon footprint (and operational energy cost) of the pilot test-bed when digital technologies (PEN) are deployed. It will also study the response of the users of the proposed monitoring and control system. As part of this research project, we will establish an autonomous self learning network of the sensors, energy consuming devices and users of energy. Self descriptive devices will be enabled to send meta-data describing relevant details of their energy consumption and context (time, task urgency etc.). The network will collect the data and create an energy consumption knowledge-base. The novel middleware will be incorporated that will run the modules of self learning and decision making to trigger actions that will shape the energy demand using specified goals. For this purpose, we will use the University of Surrey campus as initial test-bed.Technological interventions are more likely to achieve the intended energy savings if the interventions are designed with an understanding of how users view and interact with their energy systems. Within psychology, a wealth of research is available which shows that the type and format of information given to users can have a strong influence on their response. We know very little about how individuals may respond to flexible intelligent systems. We aim to examine the behavioural responses to the implementation of intelligent technologies that aim to reduce energy use in buildings.There are various ways of incentivising consumers to change load patterns. One of them is through financial models aimed at fostering the demand responsiveness of consumers. Those consumers who proactively engage in reducing or shifting their loads and significantly react to price signals should be rewarded by paying less for their electricity consumption. Part of this research will focus on the development of a financial model for an incentive/payment scheme and testing such financial models on the campus test-bed.As an outcome of the research we will deliver a pilot test bed for the autonomous and self learning Persuasive Energy-conscious Network. The psychological studies will be reported on likely expected behavioural responses of the users to the proposed technologies. A financial model will be implemented and its impact on energy demand transformation will be provided with quantified results of savings in terms of energy cost and CO2 emissions.The research will have targeted collaboration with the users of research such as the industrial researchers (e.g. Thales Research and Technologies), individual energy users (University students and staff) and corporate users of energy (University of Surrey's Estates and Facilities) and government bodies (Woking Borough Council) to highlight the potential of using the digital technology in meeting the requirements of these players in this research.

Our work brings together two important areas of science and engineering: wireless communications technology and glaciology. Using innovative techniques currently being developed for wireless communications to install a network of sensors, we will increase our understanding of how the world's large ice sheets will respond to climate change, while the knowledge gained by experimenting with wireless networks in an extreme environment will be of benefit to engineers developing the next generation of wireless networks such as mobile phone networks. Around the edge of the Greenland Ice Sheet are outlet glaciers, which allow ice to flow from the centre of the ice sheet into the sea. Where the ice meets the sea, icebergs are formed, and about half of the ice which leaves the ice sheet does so in this way. These glaciers are thought to be very sensitive to changes in air and ocean temperatures, but we do not yet know enough about them to be able to predict future changes, or understand those already observed. The processes leading to iceberg formation ('calving') are particularly important, but poorly understood. In particular, there is an urgent need to address the question of how changes in glacier flow ('dynamics') relate to changes in terminus position and calving rates. Does one drive the other, or is it more complex than that? To understand this, we need to know what the primary mechanisms are for calving in Greenland outlet glaciers, and we need characterise these mechanisms in a consistent, quantitative way across all such glaciers. Only then can the relevant processes be represented in computer models of the ice sheet and its outlet glaciers, allowing us to improve our predictions of how they will respond to climate change. To improve our understanding, it is vital to have detailed observations of iceberg calving events, but these are hard to obtain because of the difficulty of placing and maintaining instrumentation on the heavily-crevassed ice surface. To overcome the problem of getting the right observations, a network of expendable GPS receivers will be deployed on Helheim Glacier, an important calving glacier in south-east Greenland. Using special data processing techniques, GPS can be used to make measurements which are accurate to a few centimetres. The GPS receivers will be connected to each other and to a base station via a network of expendable, low-power wireless transceivers. The design of the network will mean that data can still be collected if parts of it are lost: it will be self-healing. The innovative nature of the network and its components make it economically and logistically possible to deploy a large number of sensors by helicopter in the calving region of the glacier. During the lifetime of the project, we expect to observe several calving events in detail. The data from the GPS receivers will be combined with other data sources, from aircraft, satellites and stereo photography, to obtain an unprecedented insight into iceberg formation. The data will be combined with computer models of ice flow, enabling various theories about iceberg formation to be explored and tested. This part of the project has the potential to deliver new science well beyond the end of the funded work.

Spectrum is a precious but scarce natural resource. In the UK, Ofcom will free up the analogue TV spectrum at 800MHz (together with the available 2.6GHz band) for 4G, which has already raised £2.34 billion for the national purse. According to Ofcom, the amount of data Britons consume on the move each month has already hit 20 million gigabytes, mainly due to users' engagement of video, TV and films while on the move. It is also a common understanding for the mobile operators that by 2020 a 1000 times increase in the system capacity will be needed to avoid mobile networks grinding to a halt. Maximising spectral efficiency, which is limited by interference and fading for wireless networks including 4G, is therefore a major issue. An emerging idea, which is championed by Alcatel-Lucent and has already received serious consideration by vendors and operators is that of a massive MIMO antenna system. This technology has the potential to unlock the issue of spectrum scarcity and to enhance spectrum usage tremendously by enabling simultaneous access of tens or hundreds of terminals in the same time-frequency resource. In order for massive MIMO technology to attain its utmost potential, it is important that various challenges in terms of channel estimation and acquisition due to pilot contamination, fast spatial-temporal variations in signal power and autonomous resource allocation, in particular in the presence of simultaneous access of a large number of users need to be addressed. The focus of this project is on tackling these fundamental challenges, by advancing aspects of information theory, estimation theory and network optimisations. In particular, we will contribute in terms of modelling massive MIMO channels underpinned by heterogeneous correlation structures; performing information theoretic analysis in terms of random matrix theory through shrinkage estimators; robust precoder design for massive MIMO in the presence of channel estimation errors; developing novel channel estimation technique in the presence of severe pilot contamination; and proposing and analysing game theoretic algorithms for autonomous resource allocation and pilot assignments. All the concepts and algorithms developed will be integrated and the radio link layer performance will be assessed using a simulation reference system based on LTE-Advanced standards and its evolution towards 5G. Industrial partners will be engaged throughout the project to ensure industrial relevance of our work.