A Methodology for the Design of Safety-Compliant and Secure Communication of Autonomous Vehicles

International audience; The automotive industry is increasing its effort towards scientific and technological innovations regarding autonomous vehicles. The expectation is a reduction of road accidents, which are too often caused by human errors. Moreover, technological solutions, such as connected autonomous vehicle platoons, are expected to help humans in emergency situations. In this context, safety and security issues do not yet have a satisfactory answer. In this paper, we address the domain of secure communication among vehicles - especially the issues related to authentication and authorization of inter-vehicular signals and services carrying safety commands. We propose a novel design methodology, where we take a contract-based approach for specifying safety, and combine it in the design flow with the use of the Arrowhead Framework to support security. Furthermore, we present the results through a demo, which employs model-based design for software implementation and the physical realization on autonomous model cars

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

Multi-Dimensional Model Based Engineering for Performance Critical Computer Systems Using the AADL

International audienceThe Architecture Analysis & Design Language, (AADL), Society of Automotive Engineers (SAE), AS5506, was developed to support quantitative analysis of the runtime architecture of the embedded software system in computer systems with multiple critical operational properties, such as responsiveness, safety-criticality, security, and reliability by allowing a model of the system to be annotated with information relevant to each of these quality concerns and AADL to be extended with analysis-specific properties. It supports modelling of the embedded software runtime architecture, the computer system hardware, and the interface to the physical environment of embedded computer systems and system of systems. It was designed to support a full Model Based Engineering lifecycle including system specification, analysis, system tuning, integration, and upgrade by supporting modelling and analysis at multiple levels of fidelity. A system can be automatically integrated from AADL models when fully specified and when source code is provided for the software components

Design and validation process of in-vehicle embedded electronic systems

In-vehicle electronic embedded systems are realized through complex distributed architectures. They have to provide a level of quality of service fixed by the market, the safety requirements, the cost requirements. Therefore their development and their production have to be based on a suitable methodology including their modelling, validation, optimisation and test. In this chapter, we identify the main characteristics of such systems. We introduce an ADL (Architecture Description Language), termed EAST-ADL that supports their description at each step of the development process. Finally, we present how to prove some properties on a suited model of an operational architecture described in this language

Automotive Intelligence Embedded in Electric Connected Autonomous and Shared Vehicles Technology for Sustainable Green Mobility

The automotive sector digitalization accelerates the technology convergence of perception, computing processing, connectivity, propulsion, and data fusion for electric connected autonomous and shared (ECAS) vehicles. This brings cutting-edge computing paradigms with embedded cognitive capabilities into vehicle domains and data infrastructure to provide holistic intrinsic and extrinsic intelligence for new mobility applications. Digital technologies are a significant enabler in achieving the sustainability goals of the green transformation of the mobility and transportation sectors. Innovation occurs predominantly in ECAS vehicles’ architecture, operations, intelligent functions, and automotive digital infrastructure. The traditional ownership model is moving toward multimodal and shared mobility services. The ECAS vehicle’s technology allows for the development of virtual automotive functions that run on shared hardware platforms with data unlocking value, and for introducing new, shared computing-based automotive features. Facilitating vehicle automation, vehicle electrification, vehicle-to-everything (V2X) communication is accomplished by the convergence of artificial intelligence (AI), cellular/wireless connectivity, edge computing, the Internet of things (IoT), the Internet of intelligent things (IoIT), digital twins (DTs), virtual/augmented reality (VR/AR) and distributed ledger technologies (DLTs). Vehicles become more intelligent, connected, functioning as edge micro servers on wheels, powered by sensors/actuators, hardware (HW), software (SW) and smart virtual functions that are integrated into the digital infrastructure. Electrification, automation, connectivity, digitalization, decarbonization, decentralization, and standardization are the main drivers that unlock intelligent vehicles' potential for sustainable green mobility applications. ECAS vehicles act as autonomous agents using swarm intelligence to communicate and exchange information, either directly or indirectly, with each other and the infrastructure, accessing independent services such as energy, high-definition maps, routes, infrastructure information, traffic lights, tolls, parking (micropayments), and finding emergent/intelligent solutions. The article gives an overview of the advances in AI technologies and applications to realize intelligent functions and optimize vehicle performance, control, and decision-making for future ECAS vehicles to support the acceleration of deployment in various mobility scenarios. ECAS vehicles, systems, sub-systems, and components are subjected to stringent regulatory frameworks, which set rigorous requirements for autonomous vehicles. An in-depth assessment of existing standards, regulations, and laws, including a thorough gap analysis, is required. Global guidelines must be provided on how to fulfill the requirements. ECAS vehicle technology trustworthiness, including AI-based HW/SW and algorithms, is necessary for developing ECAS systems across the entire automotive ecosystem. The safety and transparency of AI-based technology and the explainability of the purpose, use, benefits, and limitations of AI systems are critical for fulfilling trustworthiness requirements. The article presents ECAS vehicles’ evolution toward domain controller, zonal vehicle, and federated vehicle/edge/cloud-centric based on distributed intelligence in the vehicle and infrastructure level architectures and the role of AI techniques and methods to implement the different autonomous driving and optimization functions for sustainable green mobility.publishedVersio