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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.

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.

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.

R1T Exposed! A comprehensive teardown of Rivian's pioneering electric pickup reveals praiseworthy build quality, innovative thinking…and some lapses in manufacturability. EVs drive NVH materials innovation Skateboard platforms, high-frequency motor noise push lower dB thresholds and new countermeasure solutions. Optimizing design for additive manufacturing Avoiding the pitfalls of 3D printing requires knowing the process limitations - and how to work around them. An expert at a leading AM specialist shares insights on getting it right. Real-time processors help drive the zonal E/E revolution With its new generation of software-compatible processors, NXP aims to accelerate systems consolidation and performance.

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 Fool Self-Driving II The Navigator What will result from NHTSA's Tesla Autopilot investigation? Data Drives Driverless Truck Launch Smart diagnostics and advanced validation help support the reliability metrics required to gain confidence that autonomous trucks are ready for the road. Peering into the Distance New sensors of all types look out longer distances - and provide higher resolutions - for engineers pushing ADAS capabilities and higher-level vehicle automation. Ford Drives into SAE Level 2 Driver monitoring was an essential component to engineering the new "hands-free" BlueCruise/Active Glide enhanced ADAS system. A Chore No More? The Detroit Smart Parking Lab opens to develop and test emerging parking technology in real-world settings. Share and Share Alike The concepts of rideshare and urban mobility continue to evolve as new projects test what's possible.

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.

Recent developments in the commercialization of mobility services have brought unprecedented connectivity to the automotive sector. While the adoption of connected features provides significant benefits to vehicle owners, adversaries may leverage zero-day attacks to target the expanded attack surface and make unauthorized access to sensitive data. Protecting new generations of automotive controllers against malicious intrusions requires solutions that do not depend on conventional countermeasures, which often fall short when pitted against sophisticated exploitation attempts. In this paper, we describe some of the latent risks in current automotive systems along with a well-engineered multi-layer defense strategy. Further, we introduce a novel and comprehensive attack and performance test framework which considers state-of-the-art memory corruption attacks, countermeasures and evaluation methods.

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.

It is deemed that currently the intelligent connected vehicle (ICV) is in its early stage of development, and it will go through multiple development stages in the future to realize its final goal—autonomous driving. Based on the existing ICV researches, this paper believes that ICV can be used to improve the efficiency and safety of freeway. The current research of ICV has two main directions: one focuses on the traffic flow characteristics of vehicles with different attributes, the other is concerned with using ICV to reduce congestion. From the policies issued by countries around the world and the development plans promoted by major vehicle manufacturers, the future development trends and challenges of ICV are analyzed. ICV must overcome all the shortcomings to achieve its final goal, including insufficient hardware capabilities or excessive cost, and the degree of intelligence that needs to be improved.

What standardization is needed to ensure that quantum technologies do not pose an unacceptable risk from an automotive cybersecurity perspective? Click here to access the full SAE EDGETM Research Report portfolio.

Editorial Fool Self-Driving The Navigator The end of vehicle ownership Sanitary Solutions for AVs Gentex engineers are bridging mobility and medical technologies to tackle vital public-health issues of vehicle cabin cleanliness. 'Software, Start Your Engines' The 2021 Indy Autonomous Challenge is a high-speed laboratory for advancing automated driving. Getting to the 'Core' of AV Thermal Management Data-gobbling processors require new cooling solutions - and the AV industry needs standards, says a veteran engineer. Autonomy Takes Off-highway Integrating automation systems in mining, agricultural and construction machines can increase safety and productivity in the field and bring significant economic benefits. Boaring in on Vehicle-to-Animal Road Safety Researchers are using micro-Doppler radar, neural nets and machine learning to protect drivers from the wild critters that enter the road.

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 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.