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Functionalities such as automated driving, connectivity and cyber-security have gained increasing importance over the past few years. The importance of these functionalities will continue to grow as these cutting-edge technologies mature and market acceptance increases.

Reviewer Acknowledgment

Organized in cooperation with SAE International, AVL’s International Commercial Powertrain Conference- ICPC, happens every two years. It is the premier forum for truck, agricultural and construction equipment manufacturers to discuss powertrain technology challenges and solutions across their industries. This event offers a unique opportunity for engineers to address the synergy effects and distinctive characteristics of commercial vehicles, agricultural tractors and non-road vehicles, and industrial machinery. In 2017, the 9th ICPC focused on alternative powertrain technologies and innovations improving operating efficiency. These proceedings focus on: • Future challenges for engines and emissions • Smart Technologies Changing Farming • Cyber Physical Systems in Agriculture Business • OEM View of the Future of the Construction Machinery Industry • Powertrain Developments • CO2 Reduction • CVT Transmission Platform Technology • Autonomous and Connected Trucks

Abstract In the automotive domain, the overall complexity of technical components has increased enormously. Formerly isolated, purely mechanical cars are now a multitude of cyber-physical systems that are continuously interacting with other IT systems, for example, with the smartphone of their driver or the backend servers of the car manufacturer. This has huge security implications as demonstrated by several recent research papers that document attacks endangering the safety of the car. However, there is, to the best of our knowledge, no holistic overview or structured description of the complex automotive domain. Without such a big picture, distinct security research remains isolated and is lacking interconnections between the different subsystems. Hence, it is difficult to draw conclusions about the overall security of a car or to identify aspects that have not been sufficiently covered by security analyses.

Abstract In the pursuit of advancing autonomous vehicles (AVs), data-driven algorithms have become pivotal in replacing human perception and decision-making. While deep neural networks (DNNs) hold promise for perception tasks, the potential for catastrophic consequences due to algorithmic flaws is concerning. A well-known incident in 2016, involving a Tesla autopilot misidentifying a white truck as a cloud, underscores the risks and security vulnerabilities. In this article, we present a novel threat model and risk assessment (TARA) analysis on AV data storage, delving into potential threats and damage scenarios. Specifically, we focus on DNN parameter manipulation attacks, evaluating their impact on three distinct algorithms for traffic sign classification and lane assist.

Abstract Automotive software is increasingly complex and critical to safe vehicle operation, and related embedded systems must remain up to date to ensure long-term system performance. Update mechanisms and data modification tools introduce opportunities for malicious actors to compromise these cyber-physical systems, and for trusted actors to mistakenly install incompatible software versions. A distributed and stratified “black box” audit trail for automotive software and data provenance is proposed to assure users, service providers, and original equipment manufacturers (OEMs) of vehicular software integrity and reliability. The proposed black box architecture is both layered and diffuse, employing distributed hash tables (DHT), a parity system and a public blockchain to provide high resilience, assurance, scalability, and efficiency for automotive and other high-assurance systems.

Abstract The United Nation Economic Commission for Europe (UNECE) Regulation 155—Cybersecurity and Cybersecurity Management System (UN R155) mandates the development of cybersecurity management systems (CSMS) as part of a vehicle’s lifecycle. ...Due to the focus of R155 and its suggested implementation guideline, ISO/SAE 21434:2021—Road Vehicle Cybersecurity Engineering, mainly centering on the alignment of cybersecurity risk management to the vehicle development lifecycle, there is a gap in knowledge of proscribed activities for validation and verification testing. ...An inherent component of the CSMS is cybersecurity risk management and assessment. Validation and verification testing is a key activity for measuring the effectiveness of risk management, and it is mandated by UN R155 for type approval.

As a promising strategic industry group that is rapidly evolving around the world, autonomous vehicle is entering a critical phase of commercialization from demonstration to end markets. The global automotive industry and governments are facing new common topics and challenges brought by autonomous vehicle, such as how to test, assess, and administrate the autonomous vehicle to ensure their safe running in real traffic situations and proper interactions with other road users. Starting from the facts that the way to autonomous driving is the process of a robot or a machine taking over driving tasks from a human. This paper summarizes the main characteristics of autonomous vehicle which are different from traditional one, then demonstrates the limitations of the existing certification mechanism and related testing methods when applied to autonomous vehicle.

Abstract Connected autonomous vehicles that employ internet connectivity are technologically complex, which makes them vulnerable to cyberattacks. Many cybersecurity researchers, white hat hackers, and black hat hackers have discovered numerous exploitable vulnerabilities in connected vehicles. ...This study expanded the technology acceptance model (TAM) to include cybersecurity and level of trust as determinants of technology acceptance. This study surveyed a diverse sample of 209 licensed US drivers over 18 years old.

Abstract With the recent advancement in technologies, researchers worldwide have a growing interest in unmanned aerial vehicles (UAVs). The last few years have been significant in terms of its global awareness, adoption, and applications across industries. In UAV-aided wireless networks, there are some limitations in terms of power consumption, data computation, data processing, endurance, and security. So, the idea of UAVs and Edge or Fog computing together deals with the limitations and provides intelligence at the network’s edge, which makes it more valuable to use in emergency applications. Fog computing distributes data in a decentralized way and blockchain also works on the principle of decentralization. Blockchain, as a decentralized database, uses cryptographic methods including hash functions and public key encryption to secure the user information. It is a prominent solution to secure the user’s information in blocks and maintain privacy.

Abstract The innovations of vehicle connectivity have been increasing dramatically to enhance the safety and user experience of driving, while the rising numbers of interfaces to the external world also bring security threats to vehicles. Many security countermeasures have been proposed and discussed to protect the systems and services against attacks. To provide an overview of the current states in this research field, we conducted a systematic mapping study (SMS) on the topic area “security countermeasures of in-vehicle communication systems.” A total of 279 papers are identified based on the defined study identification strategy and criteria. We discussed four research questions (RQs) related to the security countermeasures, validation methods, publication patterns, and research trends and gaps based on the extracted and classified data. Finally, we evaluated the validity threats and the whole mapping process.

Since the early 1990’s, commercial vehicles have suffered from repeated vulnerability exploitations that resulted in a need for improved automotive cybersecurity. This paper outlines the strategies and challenges of implementing an automotive Zero Trust Architecture (ZTA) to secure intra-vehicle networks. ...This research successfully met the four requirements and demonstrated that using ZT principles in an on-vehicle network greatly improved the cybersecurity posture with manageable impact to system performance and deployment.

In the “What’s Next for Aerospace and Defense: A Vision for 2050” study, AIA, New York City-based McKinsey & Company, and other industry partners reveal a comprehensive 30-year, Industry 4.0 forecast of air travel and spaceflight based on improvements in automation and digitization, next-generation materials, alternative energy sources and storage, and increased data throughput.

This document defines an Aircraft Data Interface Function (ADIF) developed for aircraft installations that incorporate network components based on commercially available technologies. This document defines a set of protocols and services for the exchange of aircraft avionics data across aircraft networks. A common set of services that may be used to access specific avionics parameters are described. The ADIF may be implemented as a generic network service, or it may be implemented as a dedicated service within an ARINC 759 Aircraft Interface Devices (AID) such as those used with an Electronic Flight Bag (EFB). Supplement 8 includes improvements in the Aviation Data Broadcast Protocol (ADBP), adds support for the Media Independent Aircraft Messaging (MIAM) protocol, and contains data security enhancements. It also includes notification and deprecation of the Generic Aircraft Parameter Service (GAPS) protocol that will be deleted in a future supplement.

ARINC Report 679 defines the functional characteristics of an airborne server that will support Electronic Flight Bags (EFBs) and similar peripherals used in the flight deck, cabin, and maintenance applications. The document defines how EFBs will efficiently, effectively, safely, and securely connect to the airborne server in a way that offer expanded capabilities to aircraft operators. The airborne server has two main functions, first to provide specific services to connected systems, and second to provide centralized security for the EFB and its data. This document is a functional airborne server definition. It does not define the physical characteristics of the server.

Automated driving system (ADS) manufacturers, developers, and operators need to provide clear information on their safety approach to relevant stakeholders. Explainability to diverse audiences helps build trust in statements from these organizations towards the shared value of safety. A defined list of core safety topics can help set expectations when communicating deployment and use-case-specific automated vehicle (AV) safety information. The topics listed in this best practice are implementation-agnostic and broadly applicable. This best practice describes how safety is continuous and connected throughout lifecycle stages and highlights considerations when including safety metrics as part of the communicated information. It lists topics that are considered core, provides a rationale, illustrative examples where applicable, suggestions of content that could be included for the example, and lists references and industry examples for further information.

As technology and functionality of vehicle systems change, so do data recording needs. In ADS-dedicated vehicles (DV), the ADS perceives the environment and handles vehicle motion control, i.e., the dynamic driving task (DDT), as described in SAE J3016. When an ADS takes the place of a human driver, its sensing, processing, and control systems necessitate new considerations for data recording. Data recording is important to crash reconstruction, system performance investigations, and event analysis. It enables industry-wide improvements in ADS safety. This best practice makes recommendations for the ADS-DV data needed to support: (1) information about what the ADS "saw" and "did" and (2) identify the technology-relevant factors that contributed to the event.

An ADS-operated vehicle’s operational design domain (ODD) is defined by the manufacturer based on numerous factors. Research is underway at other organizations to define and organize ODD elements into taxonomies and other relational constructs. In order to enhance collaboration and communication between manufacturers and developers and transportation authorities, common terms and consistent frameworks are needed. The conceptual framework presented by Automated Vehicle Safety Consortium establishes a lexicon that can be used consistently by ADS developers and manufacturers responsible for defining their ADS ODD. A common framework and lexicon will reduce confusion, align expectations, and therefore build public trust, acceptance, and confidence.

AVSC Best Practice for Interactions Between ADS-DVs and Vulnerable Road Users (VRUs) AVSC00009202208 establishes common terminology and a baseline understanding of the challenges posed, and framework to evaluate automated driving system-dedicated vehicle (ADS-DV) interactions with VRUs. This best practice can facilitate communication among the industry and public, help calibrate expectations of all traffic participants, and improve broader acceptance of SAE level 4 and level 5 ADS-equipped vehicles.

AVSC Information Report for Change Risk Management AVSC00010202304 provides a process for change risk management for fleet-operated ADS-DVs using level 4 or 5 automation. The document addresses risks resulting from planned and unplanned changes in an ADS-DV design and/or operation. This information report is based on the concept of risk-informed decision-making. Making risk management decisions such as safety and change management, safety analysis, and safety assurance are especially applicable when moving from concept to production intent for the ADS-DV. Change Risk Management (CRM) does not replace best practices or other methods for managing safety anomalies or change management processes. It may instead be viewed as an additional resource that elaborates on how safety anomaly management and change management can be performed.