The increased connectivity of vehicles expands the attack surface of in-vehicle networks, enabling attackers to infiltrate through external interfaces and inject malicious traffic. These malicious flows often contain anomalous semantic information, potentially leading to misleading control instructions or erroneous decisions. While most semantic-based anomaly detection methods for in-vehicle networks focus on extracting semantic context, they often overlook interactions and associations between multiple semantics, resulting in a high false positive rate (FPR). To address these challenges, the Adaptive Structure Graph Attention Network Model (AS-GAT) is proposed for in-vehicle network anomaly detection. Our approach combines a semantic extractor with a continuously updated graph structure learning method based on attention weight similarity constraints. The semantic extractor identifies semantic features within messages, while the graph structure learning module adaptively updates the

Luo, Feng, Luo, Cheng, Wang, Jiajia, Li, Zhihao

J1939 Digital Annex

J1939DA_202412 (Current)12/29/2024

This document is intended to supplement the J1939 documents by offering the J1939 information in a form that can be sorted and searched for easier use

Truck and Bus Control and Communications Network Committee

Zonal Architecture: A Way of Using of the CAN Protocol

2024-36-0127

12/20/2024

In the automotive industry, the zonal architecture is a design approach that organizes a vehicle’s electronic and communication systems into specific zones. These zones group components based on their function and physical location, enabling more efficient integration and simplified communication between the vehicle’s various systems. An important aspect of this architecture is the implementation of the Controller Area Network (CAN) protocol. CAN is a serial communication protocol developed specifically for automotive applications, allowing various electronic devices within a vehicle, such as sensors, actuators, and Electronic Control Units (ECUs), to communicate with each other quickly and reliably, sharing information essential for the vehicle’s operation. However, due to its limitations, there is a need for more efficient protocols like Automotive Ethernet and Controller Area Network Flexible (CAN FD), which allow for higher transmission rates and larger data packets. To centralize

Santos, Felipe Carvalho, Silva, Antônio Lucas, Paterlini, Bruno, Pedroso, Henrique Gomes, Alves, Joyce Martins, Milani, Pedro Henrique Pires, Klepa, Rogério Bonette

Development and Simulation of an AUTOSAR Software Component for Functional Safety according to ISO 26262 Fault Detection and Safety Mechanisms

2024-36-0132

12/20/2024

In the context of advancing automotive electronic systems, ensuring functional safety as per ISO 26262 standards has become of primary importance. This paper presents the development of an AUTOSAR-compliant Software Component (SWC) applied to ISO 26262 applications. Using MATLAB/Simulink, we design and simulate a SWC that operates within the AUTOSAR architecture, focusing on fault detection and activation of safety mechanisms. The SWC is built to monitor specific system parameters and operational anomalies. Upon detecting a fault, it triggers predefined safety mechanisms to mitigate risks and ensure system integrity. The simulation focus on capability to accurately identify faults and execute safety measures effectively, thus demonstrating a practical approach to enhance automotive system safety implementation and its reuse. This paper not only highlights the importance of ISO 26262 in the automotive industry but also illustrates the feasibility of developing and integrating safety

Santiago, Frederico Victor Scoralick, dos Santos Machado, Cleberson, Imbasciati, Henrique, Costa, Silvio Romero Alves

Evaluation of Superficial Damage of Mechanical Components through Digital Image Analysis Using Deep Learning Framework

2024-36-0034

12/20/2024

Mechanical component failure often heralds superficial damage indicators such as color alteration due to overheating, texture degradation like rusting or false brinelling, spalling, and crack propagation. Conventional damage assessment relies heavily on visual inspections performed by technicians, a practice bogged down by time constraints and the subjective nature of human error. This research paper delves into the integration of deep learning methodologies to revolutionize surface damage evaluation, addressing significant bottlenecks in diagnostic precision and processing efficiency. We detail the end-to-end process of developing an intelligent inspection system: selecting appropriate deep learning architectures, annotating datasets, implementing data augmentation, optimizing hyperparameters, and deploying the model for widespread user accessibility. Specifically, the paper highlights the customization and assessment of state-of-the-art models, including EfficientNet B7 for

Cury, Rudoniel, Gioria, Gustavo, Chandrasekaran, Balaji

SAE TOMORROW TODAY: Scaling Connected Vehicles with Over-The-Air Updates

1349212/18/2024

As the automotive world shifts toward fully software-defined vehicles (SDVs), many OEMs are hesitant to embrace a consumer-driven model for over-the-air (OTA) updates. Enter Sibros, a company offering holistic OTA software that enables automakers to achieve scalable, software-defined mobility. By providing AI-powered insights that deliver continuous product and service enhancements, OEMs can harness Sibros' single no-code platform to monitor, control and optimize SDVs, thus accelerating time-to-market, reducing code defects and enabling hundreds of connected vehicle use cases at global scale. This presents unique value for consumers, OEMs, commercial fleet operators, and even off-road sectors like agriculture and mining. To learn more, we sat down with Hemant Sikaria, CEO & Co-Founder, Sibros, to discuss the impact of his company's groundbreaking technology, how insurance and regulation come into play, and the importance of robust security measures to ensure the responsible growth of

Hineman, Marcie

An Integrated and Miniaturized Multi-Channel Distributed Cooperative Spectrum Sensing Technology Based on Zynq

2024-01-7041

12/13/2024

In response to the escalating demand for high-performance, miniaturized, and integrated radio frequency (RF) systems, this research explores the application of the Zynq UltraScale+ RFSoC XCZU47DR chip in the realm of integrated RF transceiver technology. An 8-channel, 4.8Gsps multi-channel distributed collaborative spectrum sensing architecture has been designed, incorporating lightweight IQ neural network, which comprises a convolutional layer, three Bottleneck Units (BNU), a Global Average Pooling (GAP) layer, and a Fully Connected (FC) layer. Notably, each BNU encapsulates one or two inverted bottleneck residual blocks that integrate the concepts of inverted residual blocks and linear bottlenecks. The parameter counts and computational complexity associated with the convolution operation are significantly reduced to merely 11.89% of those required by traditional networks. The performance metrics of the hardware circuit were validated through a constructed test system. Within a 2GHz

Chen, Wangjie, Yang, Jian, Zhu, Weiqiang, Shi, Songhua, Zhou, Mingyu, Fan, Zhenhong

Diagnostics of Automotive Service-Oriented Architectures with SOVD

2024-01-7036

12/13/2024

The term Software-Defined Vehicle (SDV) describes the vision of software-driven automotive development, where new features, such as improved autonomous driving, are added through software updates. Groups like SOAFEE advocate cloud-native approaches – i.e., service-oriented architectures and distributed workloads – in vehicles. However, monitoring and diagnosing such vehicle architectures remain largely unaddressed. ASAM’s SOVD API (ISO 17978) fills this gap by providing a foundation for diagnosing vehicles with service-oriented architectures and connected vehicles based on high-performance computing units (HPCs). For service-oriented architectures, aspects like the execution environment, service orchestration, functionalities, dependencies, and execution times must be diagnosable. Since SDVs depend on cloud services, diagnostic functionality must extend beyond the vehicle to include the cloud for identifying the root cause of a malfunction. Due to SDVs’ dynamic nature, vehicle systems

Boehlen, Boris, Fischer, Diana, Wang, Jue

A Fuzz Testing Method Based on DDPM for Intelligent Connected Vehicles CAN Communication

2024-01-7044

12/13/2024

Modern vehicles are increasingly integrating electronic control units (ECUs), enhancing their intelligence but also amplifying potential security threats. Vehicle network security testing is crucial for ensuring the safety of passengers and vehicles. ECUs communicate via the in-vehicle network, adhering to the Controller Area Network (CAN) bus protocol. Due to its exposed interfaces, lack of data encryption, and absence of identity authentication, the CAN network is susceptible to exploitation by attackers. Fuzz testing is a critical technique for uncovering vulnerabilities in CAN network. However, existing fuzz testing methods primarily generate message randomly, lacking learning from the data, which results in numerous ineffective test cases, affecting the efficiency of fuzz testing. To improve the effectiveness and specificity of testing, understanding of the CAN message format is essential. However, the communication matrix of CAN messages is proprietary to the Original Equipment

Shen, Lin, Xiu, Jiapeng, Zhang, Zhuopeng, Yang, Zhengqiu

Automotive Grade Coaxial Cable Performance Specification

USCAR29 (Historical)

12/06/2024

This document specifies dimensional, functional and visual requirements for Automotive grade coaxial cable. This material will be designated AG for general-purpose automotive applications or AG LL for low loss applications. It is the responsibility of the user of this cable to verify the suitability of the selected product (based on dimensional, mechanical, electrical and environmental requirements) for its intended application. It is the responsibility of the supplier to retain and maintain records as evidence of compliance to the requirements detailed in this standard

USCAR

A Method for HPR Critical Routes Identification and Evaluation

2024-28-0150

12/05/2024

Heavy-duty vehicles, particularly those towing higher weights, require a continuous/secondary braking system. While conventional vehicles employ Retarder or Engine brake systems, electric vehicles utilize recuperation for continuous braking. In a state where HV Battery is at 100% of SOC, recuperated energy from vehicle operation is passed on to HPR and it converts electrical energy into waste heat energy. This study focuses on identification of routes which are critical for High Power Brake Resistors (HPRs), by analyzing the elevation data of existing charging stations, the route’s slope distribution, and the vehicle’s battery SOC. This research ultimately suggests a method to identify HPR critical vehicle operational routes which can be useful for energy efficient route planning algorithms, leading to significant cost savings for customers and contributing to environmental sustainability

Thakur, Shivam, Salunke, Omkar, Ambuskar, Mandar, Pandey, Lokesh

Implementation of a Hybrid Hardware-in-the-Loop (HIL) Test System for Automotive Software Validation and Verification

2024-28-0252

12/05/2024

The automotive industry relies heavily on software to enhance safety, performance, and user experience. The increasing complexity of automotive software demands rigorous testing methodologies. Ensuring the quality and reliability of this software is critical. In this paper, an innovative approach to software validation and verification using a Hybrid Hardware-In-the-Loop (HIL) test system has been proposed. This methodology integrates diverse hardware and software tools to establish a flexible and efficient testing environment. HIL environment can evaluate Device Under Test (DUT) with minimal alterations. This comprehensive solution includes the development of test strategies, plant model simulation, and compliance assurance, all in accordance with automotive standards such as ASPICE, ISO26262. Introduction of a Personality module for Automotive ECU (DUT), enables testing of multiple products using the same HIL setup. This is achieved by loading a DUT-specific signal mapping

Yadav, Vikaskumar, Bhade, Nilesh

Strategic Utilization of Digital Twins for Examining Elastic Attack Surfaces and Replicating Attack Scenarios for Vulnerability Analysis on Road Vehicle Components

2024-28-0256

12/05/2024

As vehicles adopt software-centric architectures, assessing vehicle software behavior becomes more complex, which can lead to the exploitation of overlooked or untreated vulnerabilities. Using these backdoors, attacks frequently targeted automotive products for malicious reasons. Automotive security incident management involves continuous monitoring of incidents and vulnerabilities. However, it faces challenges in reproducing attacks and revalidating security goals. The lack of visualization of attack scenarios, and vectors, and the knowledge required to replicate attacks hinders vulnerability assessment. The proposed approach aims to improve vulnerability assessment and document residual risks. It promotes replicating attack scenarios using cyber digital twins to support threat modeling, risk assessment, and threat analysis. The research paper focuses on utilizing digital twins for cybersecurity incident response, threat monitoring, and vulnerability exploitation by examining elastic

Venkatachalapathy, Sreenikethana

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