
Welsh Ambulance Services NHS Trust
Welsh Ambulance Services NHS Trust
1 Projects, page 1 of 1
assignment_turned_in Project2020 - 2024Partners:Lancashire Teaching Hospitals NHS Foundation Trust, Autonomous Drivers Alliance, Bradford Teaching Hospitals, Lero, CLAWAR Ltd +75 partnersLancashire Teaching Hospitals NHS Foundation Trust,Autonomous Drivers Alliance,Bradford Teaching Hospitals,Lero,CLAWAR Ltd,PUBLIC HEALTH ENGLAND,Shadow Robot Company Ltd,Lero (The Irish Software Research Ctr),GoSouthCoast,Ocado Technology,TechnipFMC (International),Bristol Robotics Laboratory,Health & Social Care Information Centre,Sheffield Children's NHS Foundation Trust,Autonomous Drivers Alliance,Thales UK Limited,CRODA EUROPE LTD,KUKA Robotics UK Limited,UCF,Connected Places Catapult,Thales (United Kingdom),CRODA EUROPE LIMITED,Milton Keynes Hospital,Consequential Robotics Ltd,PHE,Defence Science & Tech Lab DSTL,GoSouthCoast,Ocado Technology,Lancashire & South Cumbria NHS Fdn Trust,ATACC group,Connected Places Catapult,KUKA Robotics UK Limited,Chartered Inst of Ergo & Human Factors,NHS Digital,Defence Science & Tech Lab DSTL,Bristol Robotics Laboratory,Lancashire Teaching Hospitals NHS Trust,Kompai Robotics,Advanced Manufacturing Research Centre,Robert Bosch (Germany),National Institute of Informatics,Sheffield Childrens NHS Foundation Trust,University of Western Australia,ClearSy,Cyberselves Universal Limited,Public Health England,CLAWAR Ltd,UWA,National Institute of Informatics,ATACC group,ClearSy,Croda (United Kingdom),TechnipFMC (France),Advanced Manufacturing Research Centre,DHSC,RAC Foundation,University of York,Kompai Robotics,Defence Science and Technology Laboratory,Bradford Teaching Hospitals NHS Foundation Trust,Consequential Robotics (to be replaced),National Institute of Informatics,Cyberselves Universal Limited,Welsh Ambulance Services NHS Trust,IAM RoadSmart,ADVANCED MANUFACTURING RESEARCH CENTRE,Lancashire and South Cumbira NHS Trust,IAM RoadSmart,Shadow Robot (United Kingdom),Bradford Teaching Hospitals,University of York,KUKA (United Kingdom),Welsh Ambulance Services NHS Trust,RAC Foundation for Motoring,Robert Bosch (Germany),THALES UK LIMITED,Resilient Cyber Security Solutions,Resilient Cyber Security Solutions,University of Central Florida,Milton Keynes HospitalFunder: UK Research and Innovation Project Code: EP/V026747/1Funder Contribution: 3,063,680 GBPImagine a future where autonomous systems are widely available to improve our lives. In this future, autonomous robots unobtrusively maintain the infrastructure of our cities, and support people in living fulfilled independent lives. In this future, autonomous software reliably diagnoses disease at early stages, and dependably manages our road traffic to maximise flow and minimise environmental impact. Before this vision becomes reality, several major limitations of current autonomous systems need to be addressed. Key among these limitations is their reduced resilience: today's autonomous systems cannot avoid, withstand, recover from, adapt, and evolve to handle the uncertainty, change, faults, failure, adversity, and other disruptions present in such applications. Recent and forthcoming technological advances will provide autonomous systems with many of the sensors, actuators and other functional building blocks required to achieve the desired resilience levels, but this is not enough. To be resilient and trustworthy in these important applications, future autonomous systems will also need to use these building blocks effectively, so that they achieve complex technical requirements without violating our social, legal, ethical, empathy and cultural (SLEEC) rules and norms. Additionally, they will need to provide us with compelling evidence that the decisions and actions supporting their resilience satisfy both technical and SLEEC-compliance goals. To address these challenging needs, our project will develop a comprehensive toolbox of mathematically based notations and models, SLEEC-compliant resilience-enhancing methods, and systematic approaches for developing, deploying, optimising, and assuring highly resilient autonomous systems and systems of systems. To this end, we will capture the multidisciplinary nature of the social and technical aspects of the environment in which autonomous systems operate - and of the systems themselves - via mathematical models. For that, we have a team of Computer Scientists, Engineers, Psychologists, Philosophers, Lawyers, and Mathematicians, with an extensive track record of delivering research in all areas of the project. Working with such a mathematical model, autonomous systems will determine which resilience- enhancing actions are feasible, meet technical requirements, and are compliant with the relevant SLEEC rules and norms. Like humans, our autonomous systems will be able to reduce uncertainty, and to predict, detect and respond to change, faults, failures and adversity, proactively and efficiently. Like humans, if needed, our autonomous systems will share knowledge and services with humans and other autonomous agents. Like humans, if needed, our autonomous systems will cooperate with one another and with humans, and will proactively seek assistance from experts. Our work will deliver a step change in developing resilient autonomous systems and systems of systems. Developers will have notations and guidance to specify the socio-technical norms and rules applicable to the operational context of their autonomous systems, and techniques to design resilient autonomous systems that are trustworthy and compliant with these norms and rules. Additionally, developers will have guidance to build autonomous systems that can tolerate disruption, making the system usable in a larger set of circumstances. Finally, they will have techniques to develop resilient autonomous systems that can share information and services with peer systems and humans, and methods for providing evidence of the resilience of their systems. In such a context, autonomous systems and systems of systems will be highly resilient and trustworthy.
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