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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 Connected vehicles and intelligent transportation systems are currently evolving into highly interconnected digital environments. Due to the interconnectivity of different systems and complex communication flows, a joint risk analysis for combining safety and security from a system perspective does not yet exist. We introduce a novel method for joint risk assessment in the automotive sector as a combination of the Diamond Model, Failure Mode and Effects Analysis (FMEA), and Factor Analysis of Information Risk (FAIR). These methods have been sequentially composed, which results in a comprehensive risk management approach to information security in an intelligent transport system (ITS). The Diamond Model serves to identify and structurally describe threats and scenarios, the widely accepted FMEA provides threat analysis by identifying possible error combinations, and FAIR provides a quantitative estimation of probabilities for the frequency and magnitude of risk events.

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.

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.

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.

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.

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.

SAE EDGE Research Reports provide examinations significant topics facing mobility industry today including Connected Automated Vehicle Technologies Electrification Advanced Manufacturing

Breathing Life into Artificial Intelligence and Next Generation Autonomous Aerospace Systems Robotic Rotational Molding Creates New Opportunities for Military and Aerospace Applications Rim-Driven Electric Aircraft Propulsion High-Speed Midwave Infrared Cameras Enable Military Test Range Tracking System What Today's Advances in Radar Technology Mean for Testing and Training Tackling Ruggedization Challenges for RF Communications in Software Defined Radios AUVSI XPONENTIAL 2023 The Blueprint for Autonomy Multi-Scale Structuring of the Polar Ionosphere Understanding a radically new sensing capability for polar ionospheric science introduced by observational evidence recently provided by the electronically steerable Resolute Bay Incoherent Scatter Radar (RISR). Stepped-Frequency Distributed Radar for Through-the-Wall Sensing A technical analysis of the effectiveness of distributed radar for through-the-wall sensing applications.

Reverse Engineering the Boeing E-3 Sentry's Secondary Flight Controls Vanadium - A Green Metal Critical to Aerospace and Clean Energy Thrust in Space - The Nuances of Thruster Valve Design 3D Printing Aerodynamic Improvements Cryogenic-Capable Isolators Improve the Performance of Millimeter-Wave Systems by Lowering Noise Levels Detection with Quantum Radar A new radar prototype utilizes quantum entanglement as a method of object detection. Preliminary Development of an Integrated Mobility, Lethality, and Survivability Soldier Performance Testing Platform Developing a methodology that incorporates objective measures of performance and is sensitive to changes in soldier-system equipment could help guide equipment manufacturers during product development and acquisition. Bore Elevation and Azimuth Measurement System (Beams) Newly developed laser apparatus verifies that the pointing accuracy requirement of a weapon's fire control system is met.

Powering Better Battlefield Drones Using Low-Frequency Broadband Sonar on UUVs Experimenting in Realistic Environments Gets NewTechnology to Warfighters Designing Rugged SWaP-Optimized MOSA Solutions for UUVs Does Your UAV Program Need a Transponder? Understanding the Requirements and Guidelines Developing New Anti-Drone Radar Technology Deceiving the Enemy: These Are the Drones You Are Looking For By developing UAVs for physical deception roles to shape an adversary's ability to visually observe and orient to situations, the US military can decrease risk to air and ground combatants during mission execution by causing adversaries to expend resources, delay their reactions, or react incorrectly to tactical situations.

How Thunderbolt 4 Helps Bring Fault-Tolerant, Distributed Systems to Market Delivering Operational Energy to Enhance Warfighter Capability Optoelectronic Analog Signal Transmission Takes Center Stage Amidst Aerospace and Defense Innovation Shaking Outside the Box to Advance Flight Research An Introduction to Quantum Computing How Laser Communications Innovation is Finally Coming of Age and Driving Innovation in Defense Spatial Calibration for Accurate Long Distance Measurement Using Infrared Cameras A new spatial calibration procedure has been introduced for infrared optical systems developed for cases where camera systems are required to be focused at distances beyond 100 meters. Towards Greater Sensitivity: A Brief FTIR and Infrared-Based Cavity Ring Down Spectroscopy Comparative Study A presentation of work comparing efficacy of a traditional IR method used as a standard within the U.S.

Hundreds of aerospace executives, engineers, scientists, and academics are gathering in London this week for Aerospace Systems and Technology Conference (ASTC) 2018 from SAE International in Warrendale, Pennsylvania. Discussions during the three-day industry event center on the theme of innovating air mobility. Aerospace thought leaders are at ASTC discussing current challenges, the latest enabling technologies, and future opportunities, including those related to urban air mobility (UAM) and supersonic aircraft.

The separation of cybersecurity considerations in RMTO is barely considered, as so far, most available research and activities are mainly focused on AV. ...The main focus of this paper is addressing RMTO cybersecurity utilising an adaptable security-by-design approach, although security-by-design is still in the infant state within automotive cybersecurity. ...The main focus of this paper is addressing RMTO cybersecurity utilising an adaptable security-by-design approach, although security-by-design is still in the infant state within automotive cybersecurity. An adaptable security-by-design approach for RMTO covers Security Engineering Life-cycle, Logical Security Layered Concept, and Security Architecture.

October 29-31, 2019 │ Novi, MI

Innovations in Mobility: Aerospace Digital Summitaerospace mobility leaders convene leverage cutting-edge technology, design, develop safety measures, integrate current regulations, suggest future policies, expand markets, diversify revenue streams.

October 29-31, 2019 │ Novi, MI

Consequently, rise of this technological trend is bringing forth safety and cybersecurity challenges in form of new threats, hazards and vulnerabilities. As per the recent UN vehicle regulation 155, several risk-based security models and assessment frameworks have been proposed to counter the growing cybersecurity issues, however, the high budgetary cost to develop the tool and train personnel along with high risk of leakage of trade secrets, hinders the automotive manufacturers from adapting these third party solutions. ...As per the recent UN vehicle regulation 155, several risk-based security models and assessment frameworks have been proposed to counter the growing cybersecurity issues, however, the high budgetary cost to develop the tool and train personnel along with high risk of leakage of trade secrets, hinders the automotive manufacturers from adapting these third party solutions.