Simulation of Mixed Critical In-vehicular Networks

Future automotive applications ranging from advanced driver assistance to autonomous driving will largely increase demands on in-vehicular networks. Data flows of high bandwidth or low latency requirements, but in particular many additional communication relations will introduce a new level of complexity to the in-car communication system. It is expected that future communication backbones which interconnect sensors and actuators with ECU in cars will be built on Ethernet technologies. However, signalling from different application domains demands for network services of tailored attributes, including real-time transmission protocols as defined in the TSN Ethernet extensions. These QoS constraints will increase network complexity even further. Event-based simulation is a key technology to master the challenges of an in-car network design. This chapter introduces the domain-specific aspects and simulation models for in-vehicular networks and presents an overview of the car-centric network design process. Starting from a domain specific description language, we cover the corresponding simulation models with their workflows and apply our approach to a related case study for an in-car network of a premium car

Robust and secure resource management for automotive cyber-physical systems

2022 Spring.Includes bibliographical references.Modern vehicles are examples of complex cyber-physical systems with tens to hundreds of interconnected Electronic Control Units (ECUs) that manage various vehicular subsystems. With the shift towards autonomous driving, emerging vehicles are being characterized by an increase in the number of hardware ECUs, greater complexity of applications (software), and more sophisticated in-vehicle networks. These advances have resulted in numerous challenges that impact the reliability, security, and real-time performance of these emerging automotive systems. Some of the challenges include coping with computation and communication uncertainties (e.g., jitter), developing robust control software, detecting cyber-attacks, ensuring data integrity, and enabling confidentiality during communication. However, solutions to overcome these challenges incur additional overhead, which can catastrophically delay the execution of real-time automotive tasks and message transfers. Hence, there is a need for a holistic approach to a system-level solution for resource management in automotive cyber-physical systems that enables robust and secure automotive system design while satisfying a diverse set of system-wide constraints. ECUs in vehicles today run a variety of automotive applications ranging from simple vehicle window control to highly complex Advanced Driver Assistance System (ADAS) applications. The aggressive attempts of automakers to make vehicles fully autonomous have increased the complexity and data rate requirements of applications and further led to the adoption of advanced artificial intelligence (AI) based techniques for improved perception and control. Additionally, modern vehicles are becoming increasingly connected with various external systems to realize more robust vehicle autonomy. These paradigm shifts have resulted in significant overheads in resource constrained ECUs and increased the complexity of the overall automotive system (including heterogeneous ECUs, network architectures, communication protocols, and applications), which has severe performance and safety implications on modern vehicles. The increased complexity of automotive systems introduces several computation and communication uncertainties in automotive subsystems that can cause delays in applications and messages, resulting in missed real-time deadlines. Missing deadlines for safety-critical automotive applications can be catastrophic, and this problem will be further aggravated in the case of future autonomous vehicles. Additionally, due to the harsh operating conditions (such as high temperatures, vibrations, and electromagnetic interference (EMI)) of automotive embedded systems, there is a significant risk to the integrity of the data that is exchanged between ECUs which can lead to faulty vehicle control. These challenges demand a more reliable design of automotive systems that is resilient to uncertainties and supports data integrity goals. Additionally, the increased connectivity of modern vehicles has made them highly vulnerable to various kinds of sophisticated security attacks. Hence, it is also vital to ensure the security of automotive systems, and it will become crucial as connected and autonomous vehicles become more ubiquitous. However, imposing security mechanisms on the resource constrained automotive systems can result in additional computation and communication overhead, potentially leading to further missed deadlines. Therefore, it is crucial to design techniques that incur very minimal overhead (lightweight) when trying to achieve the above-mentioned goals and ensure the real-time performance of the system. We address these issues by designing a holistic resource management framework called ROSETTA that enables robust and secure automotive cyber-physical system design while satisfying a diverse set of constraints related to reliability, security, real-time performance, and energy consumption. To achieve reliability goals, we have developed several techniques for reliability-aware scheduling and multi-level monitoring of signal integrity. To achieve security objectives, we have proposed a lightweight security framework that provides confidentiality and authenticity while meeting both security and real-time constraints. We have also introduced multiple deep learning based intrusion detection systems (IDS) to monitor and detect cyber-attacks in the in-vehicle network. Lastly, we have introduced novel techniques for jitter management and security management and deployed lightweight IDSs on resource constrained automotive ECUs while ensuring the real-time performance of the automotive systems

Design of in-vehicle networked control system architectures through the use of new design to cost and weight processes : innovation report

Over the last forty years, the use of electronic controls within the automotive industry has grown considerably. In-vehicle network technologies such as the Controller Area Network (CAN) and Local Interconnect Network (LIN) are used to connect Electronic Control Units (ECU) together, mainly to reduce the amount of wiring that would be required if hardwired integration were used. Modern passenger cars contain many networks, which means that for the architecture designer, there is an almost overwhelming number of choices on how to design/partition the system depending on factors such as cost, weight, availability of ECUs, safety, Electro-Magnetic Compatibility (EMC) etc. Despite the increasing role played by in-vehicle networks in automotive electrical architectures, its design could currently be described as a “black art”. Not only is there an almost overwhelming number of choices facing the designer, but there is currently a lack of a quantifiable process to aid decision making and there is a dearth of published literature available. NetGen is a software tool used to design CAN/J1939, LIN and FlexRay networks. For the product to remain competitive, it is desirable to have novel features over the competition. This report describes a body of work, the aim of which was to research in-vehicle network design processes, and to provide an improvement to such processes. The opportunities of customer projects and availability of customer information resulted in the scope of the research focusing on the adoption of LIN technology and whether the adoption of it could reduce the cost and weight of the target architecture. The research can therefore be seen to address two issues: firstly the general problem of network designers needing to design in-vehicle network based architectures balancing the needs of many design targets such as cost, weight etc, and secondly the commercial motivation to find novel features for the design tool, NetGen. The outcome of the research described in this report was the development of design processes that can be used for the selection of low cost and weight automotive electrical architectures using coarse information, such as that which would be easily available at the very beginning of a vehicle design programme. The key benefit of this is that a number of candidate networked architectures can be easily assessed for their ability to reduce cost and weight of the electrical architecture

Automotive embedded systems software reprogramming

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityThe exponential growth of computer power is no longer limited to stand alone computing systems but applies to all areas of commercial embedded computing systems. The ongoing rapid growth in intelligent embedded systems is visible in the commercial automotive area, where a modern car today implements up to 80 different electronic control units (ECUs) and their total memory size has been increased to several hundreds of megabyte. This growth in the commercial mass production world has led to new challenges, even within the automotive industry but also in other business areas where cost pressure is high. The need to drive cost down means that every cent spent on recurring engineering costs needs to be justified. A conflict between functional requirements (functionality, system reliability, production and manufacturing aspects etc.), testing and maintainability aspects is given. Software reprogramming, as a key issue within the automotive industry, solve that given conflict partly in the past. Software Reprogramming for in-field service and maintenance in the after sales markets provides a strong method to fix previously not identified software errors. But the increasing software sizes and therefore the increasing software reprogramming times will reduce the benefits. Especially if ECU’s software size growth faster than vehicle’s onboard infrastructure can be adjusted. The thesis result enables cost prediction of embedded systems’ software reprogramming by generating an effective and reliable model for reprogramming time for different existing and new technologies. This model and additional research results contribute to a timeline for short term, mid term and long term solutions which will solve the currently given problems as well as future challenges, especially for the automotive industry but also for all other business areas where cost pressure is high and software reprogramming is a key issue during products life cycle

Smart Vehicles, Technologies and Main Applications in Vehicular Ad hoc Networks

Vehicular Ad hoc NETworks (VANETs) belong to a subcategory of traditional Mobile Ad hoc NETworks (MANETs). The main feature of VANETs is that mobile nodes are vehicles endowed with sophisticated “on-board” equipments, traveling on constrained paths (i.e., roads and lanes), and communicating each other for message exchange via Vehicle-to-Vehicle (V2V) communication protocols, as well as between vehicles and fixed road-side Access Points (i.e., wireless and cellular network infrastructure), in case of Vehicle-to-Infrastructure (V2I) communications. In this chapter we will introduce the state-of-the-art of recent technologies used in vehicular networks, specifically for smart vehicles, which require novel functionalities such as data communications, accurate positioning, control and decision monitoring

Conformance Testing for the AUTOSAR Standard

International audienceThe paper presents why AUTOSAR conformance tests are required, what has been achieved, and how 3 car manufacturers will use conformance tests as part of their vehicle E/E engineering process. Important topics covered are the need for conformance testing when developing a standard, the relationship between conformance and interoperability, the need for interoperability of ECUs in a vehicle, and the need to avoid diverging implementation of a standard

Trends in Automotive Communication Systems

Extended and updated version of the 2005 IEEE Proceedings paper with the same title.The use of networks for communications between the Electronic Control Units (ECU) of a vehicle in production cars dates from the beginning of the 90s. The specific requirements of the different car domains have led to the development of a large number of automotive networks such as LIN, J1850, CAN, FlexRay, MOST, etc.. This chapter first introduces the context of in-vehicle embedded systems and, in particular, the requirements imposed on the communication systems. Then, a review of the most widely used, as well as the emerging automotive networks is given. Next, the current efforts of the automotive industry on middleware technologies which may be of great help in mastering the heterogeneity, are reviewed, with a special focus on the proposals of the AUTOSAR consortium. Finally, we highlight future trends in the development of automotive communication systems