45,981 research outputs found

    A Generic System for Automotive Software Over the Air (SOTA) Updates Allowing Efficient Variant and Release Management

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    The introduction of Software Over The Air (SOTA) Updates in the automotive industry offers both the Original Equipment Manufacturer and the driver many advantages such as cost savings through inexpensive over the air bug fixes. Furthermore, it enables enhancing the capabilities of future vehicles throughout their life-cycle. However, before making SOTA a reality for safety-critical automotive functions, major challenges must be deeply studied and resolved: namely the related security risks and the required high system safety. The security concerns are primarily related to the attack and manipulation threats of wireless connected and update-capable cars. The functional safety requirements must be fulfilled despite the agility needed by some software updates and the typically high variants numbers. We studied the state of the art and developed a generic SOTA updates system based on a Server-Client architecture and covering main security and safety aspects including a rollback capability. The proposed system offers release and variant management, which is the main novelty of this work. The proof of concept implementation with a server running on a host PC and an exemplary Electric/Electronic network showed the feasibility and the benefits of SOTA updates

    Emerging privacy challenges and approaches in CAV systems

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    The growth of Internet-connected devices, Internet-enabled services and Internet of Things systems continues at a rapid pace, and their application to transport systems is heralded as game-changing. Numerous developing CAV (Connected and Autonomous Vehicle) functions, such as traffic planning, optimisation, management, safety-critical and cooperative autonomous driving applications, rely on data from various sources. The efficacy of these functions is highly dependent on the dimensionality, amount and accuracy of the data being shared. It holds, in general, that the greater the amount of data available, the greater the efficacy of the function. However, much of this data is privacy-sensitive, including personal, commercial and research data. Location data and its correlation with identity and temporal data can help infer other personal information, such as home/work locations, age, job, behavioural features, habits, social relationships. This work categorises the emerging privacy challenges and solutions for CAV systems and identifies the knowledge gap for future research, which will minimise and mitigate privacy concerns without hampering the efficacy of the functions

    D.2.1.2 First integrated Grid infrastructure

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    On Using Blockchains for Safety-Critical Systems

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    Innovation in the world of today is mainly driven by software. Companies need to continuously rejuvenate their product portfolios with new features to stay ahead of their competitors. For example, recent trends explore the application of blockchains to domains other than finance. This paper analyzes the state-of-the-art for safety-critical systems as found in modern vehicles like self-driving cars, smart energy systems, and home automation focusing on specific challenges where key ideas behind blockchains might be applicable. Next, potential benefits unlocked by applying such ideas are presented and discussed for the respective usage scenario. Finally, a research agenda is outlined to summarize remaining challenges for successfully applying blockchains to safety-critical cyber-physical systems

    Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS - a collection of Technical Notes Part 1

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    This report provides an introduction and overview of the Technical Topic Notes (TTNs) produced in the Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS (Tigars) project. These notes aim to support the development and evaluation of autonomous vehicles. Part 1 addresses: Assurance-overview and issues, Resilience and Safety Requirements, Open Systems Perspective and Formal Verification and Static Analysis of ML Systems. Part 2: Simulation and Dynamic Testing, Defence in Depth and Diversity, Security-Informed Safety Analysis, Standards and Guidelines

    Ethical and Social Aspects of Self-Driving Cars

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    As an envisaged future of transportation, self-driving cars are being discussed from various perspectives, including social, economical, engineering, computer science, design, and ethics. On the one hand, self-driving cars present new engineering problems that are being gradually successfully solved. On the other hand, social and ethical problems are typically being presented in the form of an idealized unsolvable decision-making problem, the so-called trolley problem, which is grossly misleading. We argue that an applied engineering ethical approach for the development of new technology is what is needed; the approach should be applied, meaning that it should focus on the analysis of complex real-world engineering problems. Software plays a crucial role for the control of self-driving cars; therefore, software engineering solutions should seriously handle ethical and social considerations. In this paper we take a closer look at the regulative instruments, standards, design, and implementations of components, systems, and services and we present practical social and ethical challenges that have to be met, as well as novel expectations for software engineering.Comment: 11 pages, 3 figures, 2 table
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