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On the other hand, the potential risks associated with CAV deployment related to technical vulnerabilities are safety and cybersecurity issues that may arise from flawed hardware and software. Cybersecurity and Digital Trust Issues in Connected and Automated Vehicles elaborates on these topics as unsettled cybersecurity and digital trust issues in CAVs and follows with recommendations to fill in the gaps in this evolving field. ...Cybersecurity and Digital Trust Issues in Connected and Automated Vehicles elaborates on these topics as unsettled cybersecurity and digital trust issues in CAVs and follows with recommendations to fill in the gaps in this evolving field. ...This report also highlights the importance of establishing robust cybersecurity protocols and fostering digital trust in these vehicles to ensure safe and secure deployment in our modern transportation system.

The development of highly automated driving functions (AD) recently rises the demand for so called Fail-Operational systems for native driving functions like steering and braking of vehicles. Fail-Operational systems shall guarantee the availability of driving functions even in presence of failures. This can also mean a degradation of system performance or limiting a system’s remaining operating period. In either case, the goal is independency from a human driver as a permanently situation-aware safety fallback solution to provide a certain level of autonomy. In parallel, the connectivity of modern vehicles is increasing rapidly and especially in vehicles with highly automated functions, there is a high demand for connected functions, Infotainment (web conference, Internet, Shopping) and Entertainment (Streaming, Gaming) to entertain the passengers, who should no longer occupied with driving tasks.

Hyliion shifts focus from propulsion to power generation Prime power and EV charging are two areas that can benefit from the Karno linear generator beginning later this year. Intensifying pursuit of autonomous trucks Daimler Truck and Torc have established a clear roadmap that brings SAE level 4 trucks to the U.S. market by 2027. Commercial-truck EV fleets slow to grow Even for the largest players, the underdeveloped charging ecosystem is hampering commercial-truck fleets' electrification efforts.

Advanced Autonomous Vehicles (AV) for SAE Level 3 and Level 4 functions will lead to a new understanding of the operation phase in the overall product lifecycle. Regulations such as the EU Implementing Act and the German L4 Act (AFGBV) request a continuous field surveillance, the handling of critical E/E faults and software updates during operation. This is required to enhance the Operational Design Domain (ODD) during operation, offering Functions on Demand (FoD), by increasing software features within these autonomous vehicle systems over the entire digital product lifecycle, and to avoid and reduce downtime by a malfunction of the Autonomous Driving (AD) software stack.

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.

IOOs and ADS developers agree that cost, communications, interoperability, cybersecurity, operation, maintenance, and other issues undercut efforts to deploy a comprehensive connected infrastructure.

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.

Access control enforces security policies for controlling critical resources. For V2X (Vehicle to Everything) autonomous military vehicle fleets, network middleware systems such as ROS (Robotic Operating System) expose system resources through networked publisher/subscriber and client/server paradigms. Without proper access control, these systems are vulnerable to attacks from compromised network nodes, which may perform data poisoning attacks, flood packets on a network, or attempt to gain lateral control of other resources. Access control for robotic middleware systems has been investigated in both ROS1 and ROS2. Still, these implementations do not have mechanisms for evaluating a policy's consistency and completeness or writing expressive policies for distributed fleets. We explore an RBAC (Role-Based Access Control) mechanism layered onto ROS environments that uses local permission caches with precomputed truth tables for fast policy evaluation.

Classic vehicle production had limitations in bringing the driving commands to the actuators for vehicle motion (engine, steering and braking). Steering columns, hydraulic tubes or steel cables needed to be placed between the driver and actuator. Change began with the introduction of e-gas systems. Mechanical cables were replaced by thin, electric signal wires. The technical solutions and legal standardizations for addressing the steering and braking systems, were not defined at this time. Today, OEMs are starting E/E-Architecture transformations for manifold reasons and now have the chance to remove the long hydraulic tubes for braking and the solid metal columns used for steering. X-by-wire is the way forward and allows for higher Autonomous Driving (AD) levels for automated driving vehicles. This offers new opportunities to design the vehicle in-cabin space. This paper will start with the introduction of x-by-wire technologies.

By looking into the vehicle-infrastructure cooperation (VIC) which is oriented towards intelligent, networked and integrated development, this paper analyzes and proposes the essence and development direction of Intelligent Vehicle Infrastructure Cooperation Systems (I-VICS). With an in-depth analysis of technologies of core importance to VIC and influence factors that constrain VIC development as a whole, the paper comes up with a technological route for VIC, and identifies a direction for vehicle-infrastructure cooperative development that progresses from primary to intermediate cooperation, then to advanced cooperation, and finally to full-fledged cooperation. Policy recommendations aiming at strengthening top-level design, building an integrated vehicle-infrastructure-cloud platform, expediting independence of key techs, building robust standards and regulations for VIC, enhancing workforce development as well as greater efforts at market promotion are put forward.

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.

This specification establishes process controls for the repeatable production of aerospace parts by Laser Powder Bed Fusion (L-PBF). It is intended to be used for aerospace parts manufactured using Additive Manufacturing (AM) metal alloys, but usage is not limited to such applications.

Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality.

As well, functional safety and cybersecurity constraints will increase. Electrification implies replacing energy from thermal sources with electricity from the wall and will include enhanced integration between sub-systems and components, along with higher speed in real time controls.

On-road vehicles equipped with driving automation features—where a human might not be needed for operation on-board—are entering the mainstream public space. However, questions like “How safe is safe enough?” and “What to do if the system fails?” persist. This is where remote operation comes in, which is an additional layer to the automated driving system where a human remotely assists the so-called “driverless” vehicle in certain situations. Such remote-operation solutions introduce additional challenges and potential risks as the entire vehicle-network-human now needs to work together safely, effectively, and practically. Unsettled Issues in Remote Operation for On-road Driving Automation highlights technical questions (e.g., network latency, bandwidth, cyber security) and human aspects (e.g., workload, attentiveness, situational awareness) of remote operation and introduces evolving solutions.

High on hydrogen Through its Symbio joint venture with Michelin, Faurecia expands far beyond its interior-systems base into the fuel-cell future. Simulating a faster route to ADAS and AV validation With its new cloud-based Simphera platform, dSpace responds to demand from global automated-vehicle development teams to help manage their expanding, complex workload. Innovating the methanol fuel cell Using methanol as the source fuel provides an alternative to a gaseous-hydrogen distribution and storage infrastructure, among other potential benefits. Engineering the 2022 Toyota Tundra Chief Engineer Mike Sweers talks structure, materials and a different approach to hybrid power.

Editorial Follow the money The Navigator C-V2X is finally gaining momentum in the U.S. Making the Strategic Move Into AV Testing Having built its global engineering reputation in the combustion-engine era, FEV makes a critical leap into automated-vehicle testing. Sony Jumps Into AV Sensors, Software The consumer-electronics giant leverages its innovative technologies for ADAS prototypes and partners with Hungary-based AImotive for automated-driving software. Mitigating Radar-to-Radar Interference An effective radar interference mitigation strategy should have the right balance between complexity and capability for dealing with the interferers. Amending the Automated-driving 'Constitution' SAE International's J3016 standard has been comprehensively revised with new distinctions and definitions. The Committee chairperson, Barbara Wendling, addresses the fine points behind the industry-defining - and perpetually controversial - classification for automated-driving capability.

Editorial Making Safety Standard The Navigator Sensor Monoculture is a Terrible Idea 3D-printed Radar Rises Toward Production Lunewave's unique Luneburg-lens technology aims to simplify vehicle radar arrays - and deliver better ADAS and AV performance. Accelerating Automotive Radar NXP's new, fifth-generation chipsets unleash 16-nm FinFet technology to the ADAS and AV markets. Autonomy's Computing Backbone Cloud-computing networks are speeding AV development and preparing to manage tomorrow's data-reliant AV fleets. Get in Line Evolving truck-platooning techniques are paving unique paths to high-level commercial vehicle autonomy. Ford in 'No-hands' Land BlueCruise hands-free driver-assist is available later this year for the Mustang Mach-E and F-150 pickup. ADAS-equipped Trucks Save Bucks Bosch research finds one specific driver-assistance feature may reduce costs associated with property damage by up to 35% for Class 7 and 8 trucks.

Editorial SPAC attack The Navigator Mapping the way to safe and natural automated driving Motorcycles Enter the ADAS Age The latest models from BMW, Ducati and KTM feature Bosch's new ACC setup, but further advancements will require navigating critical rider-control strategies. On the Way to SVA Aptiv says its Smart Vehicle Architecture central controller is the key to simpler, more compact and higher-performance ADAS and AV systems. New Insistence for Driver Assistance Panelists at SAE International's 2021 Government/Industry Meeting say assisted-driving technology is worthwhile - but effective driver monitoring is crucial. Flash! Lidar's Next Generation Arrives Technology solutions from new players and alliances are poised to drive down cost. Horiba MIRA's Vision for World-Class AV Testing A new autonomous vehicle development center called Assured CAV boasts a lengthy list of assets and capabilities.

Autonomous driving represents the ultimate goal of future automobile development. As a collaborative application that integrates vehicles, road infrastructure, network and cloud, autonomous driving business requires a high-degree dynamic cooperation among multiple resources such as data, computing and communications that are distributed throughout the system. In order to meet the anticipated high demand for resources and performance requirements of autonomous driving, and to ensure the safety and comfort of the vehicle users and pedestrians, a top concern of autonomous driving is to understand the system requirements for resources and conduct an in-depth analysis of the autonomous driving business. In this context, this paper presents a comprehensive analysis of the typical business for autonomous driving and establishes an analysis model for five common capabilities, i.e. collection, transmission, intelligent computing, human-machine interaction (HMI), and security.