Number Of ECUs Research Articles

Multiple Observation HMM-Based CAN Bus Intrusion Detection System for In-Vehicle Network

As modern vehicles become more intelligent and connected, the number of ECUs and communication interfaces with external networks (such as 3G/4G and Bluetooth) has increased significantly, which raises potential network security risks. Due to the absence of effective security measures, there is a frequent occurrence of cybersecurity incidents targeting vehicles, particularly the in-vehicle CAN bus network. As the main bus in the vehicle, CAN bus faces important challenges in its safety due to the lack of security mechanisms. Therefore, we propose a CAN bus intrusion detection system based on multiple observation HMM for in vehicle networks to enhance the security of the vehicle. Specifically, the proposed algorithm builds a multiple observation HMM based on the ID and data fields of normal CAN bus traffic. According to the established HMMs, we calculate the existence probability of the frame under the defined time window as the detection threshold. When the existence probability of the frame to be detected exceeds the normal threshold range, it is considered abnormal. Furthermore, we establish four common attack models based on the collected real vehicle data, and evaluate the performance of the proposed algorithm in these attack scenarios. The experimental results show that the proposed method has better detection performance than other frame by frame anomaly detection methods in four attack scenarios.

Vehicle Health Monitoring System Using CAN

Modern vehicles are integrated with more number of ECUs and sensors which make them smarter in terms of engine decisions, performance, fuel efficiency, security and stability. ECUs also provide useful data in the form of diagnostic codes via OBDII (on-board diagnostics) protocol, these codes determine a specific issue in the vehicular system which is used by service technicians to address the issues occurred. This paper deals with the exploring the potential of OBDII codes from engine ECU and compute the data on an Android device to monitor the vehicle health status in real-time. The whole idea is to provide portable diagnosis solutions and integration of such system into in-vehicle entertainment like Google’s Android Auto and Apple’s CarPlay which can be one of key component for V2X and IOVs (Internet of Vehicles).

Scalable Holistic Scheduling of Safety-critical Systems on In-vehicle TDMA Networks

Recently, the authors have proposed a scalable holistic scheduling approach for time-triggered applications on FlexRay, under end-to-end deadline and data dependency constraints. This approach divides the problem to two sub-problems that can be solved separately. The first sub-problem optimally schedules the set of messages to minimize number of used slots, and with respect to information exchanges between tasks and messages, end-to-end deadlines and FlexRay protocol constraints. The second sub-problem optimally schedules the set of tasks to minimize tasks response times, with respect to the solution returned by the first sub-problem. In this paper, our goal is to increase the scalability of our solution to each sub-problem. We propose a greedy heuristic approach for the first sub-problem that can find feasible solutions at a low runtime cost. In addition, to resolve assignment conflicts, we apply rescheduling the conflicted application with offset modification and priority promotion procedures. Furthermore, we show that the task scheduling in the second sub-problem can be divided into K independent child sub-problems, where K is the number of ECUs. Our experiments show high scalability and efficiency of our approaches comparing with our optimization-based approaches in the previous work.

Performance optimization of task intensive real time applications on multicore ECUs - a hybrid scheduler

In the current approach of Automotive electronic system design, the multicore processors have prevailed to achieve high computing performance at low thermal dissipation. Multicore processors offer functional parallelism that helps in meeting the safety critical requirements of vehicles. The number of ECUs in high-end cars could be reduced by conglomerating more functions into a multicore ECU. AUTOSAR stack has been designed to support the applications developed for multicore ECUs. The real challenges lie in adapting new design methods while developing sophisticated applications with multicore constraints. It is imperative to utilize the most of multicore computational capability towards enhancing the overall performance of ECUs. In this context the scheduling of the real time multitasking software components by the operating system is one of the key issues to be addressed. In this paper, the state of the art scheduling algorithm is reviewed and its merits and limitations are identified. A hybrid scheduler has been proposed, tested and compared with the state of the art algorithm that offers better performance in terms of CPU utilization, average response time and deadline missing rate both in normal and high load conditions.

Understanding Vehicle E/E Architecture Topologies for Automated Driving: System Partitioning and Tradeoff Parameters

Highly Automated Driving is an active research and development area in automotive market for next generation series production. The development of automated functions like Highway driving or Parking gets partitioned across Edge and Central ECU's as part of vehicle E/E network. The paper introduces typical vehicle E/E topologies with emphasis on ADAS/AD domain with multiple intra/inters connectivity options. Within the ADAS/AD domain, various E/E system architecture topologies with multiple ECU partitioning are under exploration to optimize various parameters. The paper explains multiple topologies by analyzing two example system topologies. Topology-I enables incremental approach on the top of legacy ECUs, while topology-II enables cost optimized solution. The paper also explains functional partitioning of automated driving functionality (e.g. Highway driving, Parking) within ADAS/AD domain. This involves splitting of automated function in given topology across multiple ECUs in terms of perception (camera, radar & lidar), localization, fusion, driving policy, motion planning and control. The paper lists various parameters for considerations for given topologies e.g. Number of ECUs, intra domain connection bandwidth, functional safety, incremental development with legacy ECUs, cost and ease of software development. The paper ends with summarizing of these partitioning of functions and parameters tradeoffs enabling users to analyze custom E/E architectures.