163 research outputs found

    Fault detection and diagnosis for in-vehicle networks

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    Modeling and verifying the FlexRay physical layer protocol with reachability checking of timed automata

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    In this thesis, I report on the verification of the resilience of the FlexRay automotive bus protocol's physical layer protocol against glitches during message transmission and drifting clocks. This entailed modeling a significant part of this industrially used communictation protocol and the underlying hardware as well as the possible error scenarios in fine detail. Verifying such a complex model with model-checking led me to the development of data-structures and algorithms able to handle the associated complexity using only reasonable resources. This thesis presents such data-structures and algorithms for reachability checking of timed automata. It also present modeling principles enabling the construction of timed automata models that can be efficiently checked, as well as the models arrived at. Finally, it reports on the verified resilience of FlexRay's physical layer protocol against specific patterns of glitches under varying assumptions about the underlying hardware, like clock drift.In dieser Dissertation berichte ich über den Nachweis der Resilienz des Bitübertragungsprotokolls für die physikalische Schicht des FlexRay-Fahrzeugbusprotokolls gegenüber Übertragungsfehlern und Uhrenverschiebung. Dafür wurde es notwendig, einen signifikanten Teil dieses industriell genutzten Kommunikationsprotokolls mit seiner Hardwareumgebung und die möglichen Fehlerszenarien detailliert zu modellieren. Ein so komplexes Modell mittels Modellprüfung zu überprüfen führte mich zur Entwicklung von Datenstrukturen und Algorithmen, die die damit verbundene Komplexität mit vernünftigen Ressourcenanforderungen bewältigen können. Diese Dissertation stellt solche Datenstrukturen und Algorithmen zur Erreichbarkeitsprüfung gezeiteter Automaten vor. Sie stellt auch Modellierungsprinzipien vor, die es ermöglichen, Modelle in Form gezeiteter Automaten zu konstruieren, die effizient überprüft werden können, sowie die erstellten Modelle. Schließlich berichtet sie über die überprüfte Resilienz des FlexRay-Bitübertragungsprotokolls gegenüber spezifischen Übertragungsfehlermustern unter verschiedenen Annahmen über die Hardwareumgebung, wie etwa die Uhrenverschiebung.DFG: SFB/TRR 14 "AVACS - Automatische Verifikation und Analyse komplexer Systeme

    Machine learning and blockchain technologies for cybersecurity in connected vehicles

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    Future connected and autonomous vehicles (CAVs) must be secured againstcyberattacks for their everyday functions on the road so that safety of passengersand vehicles can be ensured. This article presents a holistic review of cybersecurityattacks on sensors and threats regardingmulti-modal sensor fusion. A compre-hensive review of cyberattacks on intra-vehicle and inter-vehicle communicationsis presented afterward. Besides the analysis of conventional cybersecurity threatsand countermeasures for CAV systems,a detailed review of modern machinelearning, federated learning, and blockchain approach is also conducted to safe-guard CAVs. Machine learning and data mining-aided intrusion detection systemsand other countermeasures dealing with these challenges are elaborated at theend of the related section. In the last section, research challenges and future direc-tions are identified

    CONCEPTS AND TOOLS FOR THE TEST OF THE COMMUNICATION SUB-SYSTEM OF TIME-TRIGGERED DISTRIBUTED EMBEDDED SYSTEMS

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    ABSTRACT With the adoption of FlexRay, the time triggered paradigm has been widely accepted by the automotive industry as a means to tackle the requirements of future automotive electronics. However, when compared with traditional event-triggered systems like CAN, the benefits of higher reliability come at the cost of increased complexity during system design. In fact, to support the development of these systems adequate tool-support will be mandatory. In this paper we discuss the requirements and concepts for and present an implementation of a test and diagnosis toolset for FlexRay-based automotive distributed networks. Next to data monitoring and recording, this toolset provides facilities for fault injection and replay. Hence, the presented implementation is tailored for an embedded test and fault diagnosis and will enable an assessment of the reliability and dependability of future automotive solutions

    A framework and methods for on-board network level fault diagnostics in automobiles

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    A significant number of electronic control units (ECUs) are nowadays networked in automotive vehicles to help achieve advanced vehicle control and eliminate bulky electrical wiring. This, however, inevitably leads to increased complexity in vehicle fault diagnostics. Traditional off-board fault diagnostics and repair at service centres, by using only diagnostic trouble codes logged by conventional onboard diagnostics, can become unwieldy especially when dealing with intermittent faults in complex networked electronic systems. This can result in inaccurate and time consuming diagnostics due to lack of real-time fault information of the interaction among ECUs in the network-wide perspective. This thesis proposes a new framework for on-board knowledge-based diagnostics focusing on network level faults, and presents an implementation of a real-time in-vehicle network diagnostic system, using case-based reasoning. A newly developed fault detection technique and the results from several practical experiments with the diagnostic system using a network simulation tool, a hardware- in-the- loop simulator, a disturbance simulator, simulated ECUs and real ECUs networked on a test rig are also presented. The results show that the new vehicle diagnostics scheme, based on the proposed new framework, can provide more real-time network level diagnostic data, and more detailed and self-explanatory diagnostic outcomes. This new system can provide increased diagnostic capability when compared with conventional diagnostic methods in terms of detecting message communication faults. In particular, the underlying incipient network problems that are ignored by the conventional on-board diagnostics are picked up for thorough fault diagnostics and prognostics which can be carried out by a whole-vehicle fault management system, contributing to the further development of intelligent and fault-tolerant vehicles

    Robust and secure resource management for automotive cyber-physical systems

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    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 automotive X-by-Wire systems

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    http://www.taylorandfrancis.com/X-by-Wire is a generic term referring to the replacement of mechanical or hydraulic systems, such as braking or steering, by electronic ones. In this chapter, we analyze the real-time and dependability constraints of X-by-Wire systems, review the fault-tolerant services that are needed and the communication protocols (TTP/C, FlexRay and TTCAN) considered for use in such systems. Using a Steer-by-Wire case-study, we detail the design principles and verification methods that can be used to ensure the stringent constraints of X-by-Wire systems

    Trends in Automotive Communication Systems

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    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

    Fault Tolerant Services for Safe In-Car Embedded Systems

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    http://www.taylorandfrancis.com/Due to the increasing criticality of the functions in terms of safety, embedded automotive systems must now respect stringent dependability constraints despite the faults that may occur in a very harsh environment. In a context where critical functions are distributed over the network, the communication system plays a major role. First, we discuss the main services and functionalities that a communication system should offer for easying the design of fault-tolerant applications in the automotive context. Then, we review the features of the protocols that are currently considered for being used and, finally, we highlight areas where developments are still needed
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