The Hub will address two challenges introduced by the use of Edge Computing (EC) to support emerging AI algorithms: dealing with cyber disturbances and managing data quality. The Hub will achieve these through a unique 3x3x3x2 matrix that reflects the complexity of these systems: (1) 3 real-world application domains (2) 3 tiers of EC architecture (3) 3 ground-breaking research work streams (4) 2 industry engagement work streams Their inter-relationships will be examined by a multi-disciplinary team with track records in EC architecture (Newcastle, Cardiff, St. Andrews, UWS, Imperial, Hull), foundational AI and Data Quality (Southampton, Durham, QUB, Swansea), wireless communication (Cardiff, UWS), device malfunction, attack detection and prevention (Newcastle, Lancaster, Cardiff, Warwick), and AI security (Lancaster, Swansea, Durham, Warwick). This network will enable us to engage with regional development agencies in these areas. Applications include autonomous electric vehicles, energy security and remote healthcare. At the Newcastle Urban Observatory test-bed, a world-leading UK-funded effort collaborating with sensor system manufacturers, software companies and others, we will use interactions across 3 tiers of EC architecture: sensors (Tier 1), edge devices that control them (Tier 2), and cloud-based data storage and processing (Tier 3), to identify the benefit of these interactions in the real-world data processing. The agenda will be underpinned by activities in 5 interrelated work streams. We have strategies in: Embedding Equality, Diversity & Inclusion: We are committed to EDI policies of UKRI and EPSRC Councils and EDI policies of our members. From these, we will form our guiding principle around EDI for members to adhere to in all matters related to the Hub, including recruitment, research, workshops, project allocations, outreach activities, etc. All core committees will have an EDI champion. We will ensure that activities are fair, free from bias and preference of any kind, and uphold the respect and integrity of all members. The Hub is constituted of members from diverse ethnic backgrounds, races, and gender and has intrinsically diverse and multicultural characteristics. We will actively encourage students from under-represented groups to pursue industry-funded PhDs with the Hub. The PDRA requirement in the Hub will, while maintaining the best talent, offer equal opportunity to candidates of all backgrounds, disabilities, sexual orientations, gender, and ethnicity. The Hub will use institutional infrastructure to support the well-being of staff and members. Intellectual Property Management: While most research outcomes will be made public (e.g., software open access), some may be subject to patents. Participating universities have commercialisation offices to identify, assess, protect, manage and commercially develop IP to maximise national benefits from public investment in research, which we will use to commercialise significant outcomes. Information about services, standards used, and other technical details will be made public to attract industrial partners and to promote training in the new technologies. Non-technical press releases and notes will be available to general audiences. An in-principle agreement has been reached with consortium members that each shall retain ownership of any background IP contributed to the project and that the ownership of project-generated IP shall be shared based on respective partner contributions. Hub activities will in general follow the National Principles of Intellectual Property Management for Publicly Funded Research and this will be applied to each project managed under the feasibility fund. Non-Disclosure Agreements with commercial partners will be in place to manage sensitive information. Specific terms regarding IP will be further defined in a collaborative research agreement before the commencement of the project.

The CDT in Advanced Automotive Propulsion Systems will produce the graduates who will bring together the many technical disciplines and skills needed to allow propulsion systems to transition to a more sustainable future. By creating an environment for our graduates to research new propulsion systems and the wider context within which they sit, we will form the individuals who will lead the scientific, technological, and behavioural changes required to effect the transformation of personal mobility. The CDT will become an internationally leading centre for interdisciplinary doctoral training in this critical field for UK industrial strategy. We will train a cohort of 84 high quality research leaders, adding value to academia and the UK automotive industry. There are three key aspects to the success of the CDT - First, a diverse range of graduates will be recruited from across the range of first degrees. Graduates in engineering (mechanical, electrical, chemical), sciences (physics, chemistry, mathematics, biology), management and social sciences will be recruited and introduced to the automotive propulsion sector. The resulting skills mix will allow transformational research to be conducted. Second, the training given to this cohort, re-enforced by a strong group working ethos, will prepare the graduates to make an effective contribution to the industry. This will require training in the current and future methods (technical and commercial) used by the industry. We also need the graduates to have highly developed interpersonal skills and to be experienced in effective group working. Understanding how people and companies work is just as important as an understanding the technology. On the technology side, a broad system level understanding of the technology landscape and the relationship between the big picture and the graduate's own expertise is essential. We have designed a programme that enriches the student's knowledge and experience in these key areas. Third, underpinning all of these attributes will be the graduate's research skills, acquired through the undertaking of an intensive research project within the new £60 million Institute for Advanced Automotive Propulsion Systems (IAAPS), designed from the outset to provide a rich collaborative environment and add value to the UK economy. IAAPS will be equipped with world leading experimental facilities designed for future powertrain systems and provides dedicated space for industry and academia to collaborate to deliver research valued at over £100 million during the lifetime of the CDT. The cohort will contribute to and benefit from this knowledge development, providing opportunities to conduct research at a whole system level. This will address one of the most pressing challenges of our age - the struggle to provide truly sustainable, affordable, connected, zero emissions transport needed by both industrialised and emerging economies. To enable these benefits we request funding for 40 studentships and the infrastructure to provide a world class training environment. The university will enhance this through the funding of an additional 20 studentships and access to research facilities, together valued at £5 million. Cash and in-kind contributions from industrial partners valued at a total of £4.5 million will enhance the student experience, providing 9 fully funded PhD places and 30 half funded places. The research undertaken by the students will be co-created and supervised by our industrial partners. The people and research outputs that from the CDT will be adopted directly by these industrial partners to generate lasting real world impact.

AI applications have become pervasive: from mobile phones and home appliances to stock markets, autonomous cars, robots and drones. As AI takes over a wider range of tasks, we gradually approach the times when security laws, or policies, ultimately akin to Isaac Asimov's "3 laws of robotics" will need to be established for all working AI systems. A homonym of Asimov's first name, the project AISEC (``Artificial Intelligence Secure and Explainable by Construction"), aims to build a sustainable, general purpose, and multidomain methodology and development environment for policy-to-property secure and explainable by construction development of complex AI systems. We will create and deploy a novel framework for documenting, implementing and developing policies for complex deep learning systems by using types as a unifying language to embed security and safety contracts directly into programs that implement AI. The project will produce a development tool AISEC with infrastructure (user interface, verifier, compiler) to cater for different domain experts: from lawyers working with security experts to verification experts and system engineers designing complex AI systems. AISEC will be built, tested and used in collaboration with industrial partners in two key AI application areas: autonomous vehicles and natural language interfaces. AISEC will catalyse a step change from pervasive use of deep learning in AI to pervasive use of methods for deep understanding of intended policies and latent properties of complex AI systems, and deep verification of such systems.

The development of innovative autonomous vehicles (AV) with increased efficiency and low carbon emissions is of interest to many different organisations across the world, at both political, commercial and research levels. Economically benefits are estimated to be worth £1.5 trillion by 2025. Recognising the potential, transportation authorities are already investing heavily in studies to exploit these innovative technologies through the development of 'platooning' methods, whereby a series of vehicles run in close formation, exploiting potential energy savings created through a reduction in drag, further enabling greater mobility. In the immediate future, it is likely the freight haulage industry will be the first users to introduce autonomous technologies on a network-wide scale. The UK road network provides the ideal test bed for developing these innovative technologies, due to the complexities of adopting such systems within a highly congested network, with traffic moving at variable speeds. Ensuring AVs and platooning methods are appropriate for challenging transport systems, such as that in the UK, will enable these systems to be adopted on an international scale more easily. To date, most AV research has focused on ensuring the technical possibilities for vehicles travelling in close formation through the implementation of autonomous guidance systems. These factors are however only one area of consideration when introducing new operational methods that involve complex vehicle interactions into an already a complex transport mode. Fundamental research undertaken at the University of Birmingham (UoB) (EP/N004213/1) has shown that aerodynamic forces will, in many cases, be the governing design parameter. There is a need to understand and correctly account for the highly turbulent aerodynamic flow created around platoons and unsteady forces leading to vehicle instabilities and dangerous conditions for other road users. This proposal is concerned with the technical area of vehicle aerodynamics associated with close running vehicles and the aerodynamic interactions with other vehicles and road users. In particular the following aspects will be investigated: -Overall stability of close formation vehicles (Heavy Goods Vehicles (HGVs)), particularly the interaction of unsteady aerodynamic flows between platooning vehicles and other road users. -The aerodynamic implications in terms of stability and overall drag for vehicles moving out of alignment with other vehicles in a platoon and the interaction of overtaking vehicles. -The aerodynamic interaction of a passing platoon of HGVs with other road users leading to potential stability and safety issues. The fundamental research questions will be addressed by novel approaches: -A fundamental physical modelling programme at the UoB moving model TRAIN rig facility. Detailed measurement of vehicle surface pressure (such that aerodynamic forces can be calculated) will determine the nature of the flow field and the aerodynamic interaction of vehicles. Multi-hole pressure probe measurements will investigate the unsteady flow to determine potential stability and safety implications as a platoon passes. -Development of an analytical framework, providing a method to help industry assess the magnitude of aerodynamic loads on roadside workers and other road users. The current study is seen as a necessary precursor to the introduction of AV technologies. In depth understanding of these practical issues underpins the safe, timely and cost effective implementation of these new technologies. This project will, for the first time, address these issues, developing an understanding of aerodynamic effects, not only for platooning vehicles but also other road users interacting with the platoon on public transport systems. The national importance of AVs forms an integral part of the Government strategic vision for transport and is of considerable importance to a variety of stakeholders.

Trusted Execution Environments (TEEs) shield computations using security-sensitive data (e.g. personal data, banking information, or encryption keys) inside a secure "enclave" from the rest of the untrusted operating system. A TEE protects its data and code even if an attacker has gained full root access to the untrusted parts of the system. Today, TEEs like ARM Trustzone and Intel SGX are therefore widely used in general-purposes devices, including most laptops and smartphones. But with increasingly wide-spread use, TEEs have proven vulnerable to a number of hardware and software-based attacks, often leading to the complete compromise of the protected data. In this project, we will use capability architectures (as e.g. developed by the CHERI project) to protect TEEs against such state-of-the-art attacks. We address a wide range of threats from software vulnerabilities such as buffer overflows to sophisticated hardware attacks like fault injection. CAP-TEE will provide a strong, open-source basis for the future generation of more secure TEEs. When developing such disruptive technologies, it is key to minimise the efforts for porting existing codebases to the new system to facilitate adoption in practice. In CAP-TEE, we therefore focus on techniques to ease the transition to our capability-enabled TEE. In industrial cases studies for the automotive and rail sector, we will demonstrate how complex code written in a memory-unsafe language like C(++) can be seamlessly moved to our platform to benefit from increased security without a full redesign.