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To build secure systems of road vehicles, the cybersecurity engineering standard ISO21434[11] suggests the evaluation of vulnerabilities throughout engineering process, such as attack path analysis, system requirement stage, software architecture, design, and implementation and testing phases. ...With my analysis and practices, it is appropriate to include the common vulnerabilities that ought to be an integral part of the automotive cybersecurity engineering process. In this paper, the author would like to provide a list of vulnerabilities that might be a suggestion for threat analysis and risk assessment and propose two solutions that may be adopted directly in the V-model for security-relevant software development.

Abstract Automotive cybersecurity is steadily becoming a key factor in the worldwide adoption of connected and self-driving vehicles.

Additional complicating factors, such as cybersecurity concerns combined with a first responder’s legal authority, may pose challenges for traditional data collection.

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.

Connected vehicles can provide data from multiple sensors that monitor both the vehicle and the environment through which the vehicle is passing. The data, when shared, can be used to enhance and optimize transportation operations and management—specifically, traffic flow and infrastructure maintenance. This document describes an interface between vehicle and infrastructure for collecting vehicle/probe data. That data may represent a single point in time or may be accumulated over defined periods of time or distance, or may be triggered based on circumstance. The purpose of this document is to define an interoperable means of collecting the vehicle/probe data in support of the use cases defined herein. There are many additional use cases that may be realized based on the interface defined in this document. Note that vehicle diagnostics are not included within the scope of this document, but diagnostics-related features may be added to probe data in a future supplemental document.

Abstract With the adoption of Vehicle-to-everything (V2X) technology, security and privacy of vehicles are paramount. To avoid tracking while preserving vehicle/driver’s privacy, modern vehicular public key infrastructure provision vehicles with multiple short-term pseudonym certificates. However, provisioning a large number of pseudonym certificates can lead to an enormous growth of Certificate Revocation Lists (CRLs) during its revocation process. One possible approach to avoid such CRL growth is by relying on activation code (AC)-based solutions. In such solutions, the vehicles are provisioned with batches of encrypted certificates, which are decrypted periodically via the ACs (broadcasted by the back-end system). When the system detects a revoked vehicle, it simply does not broadcast the respective vehicle’s AC. As a result, revoked vehicles do not receive their respective AC and are prevented from decrypting their certificates.

Modern automobiles collect around 25 gigabytes of data per hour and autonomous vehicles are expected to generate more than 100 times that number. In comparison, the Apollo Guidance Computer assisting in the moon launches had only a 32-kilobtye hard disk. Without question, the breadth of in-vehicle data has opened new possibilities and challenges. The potential for accessing this data has led many entrepreneurs to claim that data is more valuable than even the vehicle itself. These intrepid data-miners seek to explore business opportunities in predictive maintenance, pay-as-you-drive features, and infrastructure services. Yet, the use of data comes with inherent challenges: accessibility, ownership, security, and privacy. Unsettled Legal Issues Facing Data in Autonomous, Connected, Electric, and Shared Vehicles examines some of the pressing questions on the minds of both industry and consumers. Who owns the data and how can it be used?

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.

Digitally enabled mobility vehicles and services, including dockless bikesharing and electric scooter sharing, are generating and collecting a growing amount of mobility data. Mobility data holds great potential to support transportation officials and their efforts to manage the public right-of-way, but the unlimited distribution of mobility data carries untested risks to privacy and public trust. The Mobility Data Collaborative™ has identified the need to improve and coordinate understanding among all parties around foundational policy and legal issues to support mobility data sharing, including privacy and contracting. The guidelines are geared towards supporting a scalable mobility data sharing framework that aligns the interests of the public and private sectors while addressing privacy, transparency, data ownership, and consumer trust.

Editorial The new 'face' of privacy The Navigator No trust in AI systems without data protection Innovation Nation In the mobility space, Israel is rivaling Silicon Valley for smarts and start-ups - and beats it in chutzpah. Autonomy in your Face Biometric technology is deemed essential to ensuring AV driving safety and advancing the user experience-if privacy issues don't derail its deployment. About Face! To win acceptance, deployment of facial-recognition technology needs to fit within a picture-perfect consumer and legal framework that balances benefits with privacy protection. The Vehicle as Gaming Device Audi spin-off Holoride uses VR to turn the back seat into an entertainment platform. BlackBerry Tech Duo Sees Emergence of Vehicle-based Platforms Though likely to provide the OS of autonomy, BlackBerry also anticipates a larger shift to automobiles as software platforms.

Editorial It's more than just a magazine The Navigator Needed: a step beyond STEM SAE AV Activities A listing of SAE International's autonomous vehicle-related offerings across the organization. Autonomy for the Masses Ford Autonomous Vehicles LLC aims to do for AVs what the Model T did for just about everyone. CEO Sherif Marakby explains. Speeding Thermal Analysis for Autonomous EVs Solving thermal challenges is vital to AEV development. Siemens PLM's new Simcenter integrated simulation package offers a high-fidelity, easy-to-use solution. New Mobility's Mega-Mappers Most believe ultrahigh-definition mapping is crucial to make high-level automated driving possible. Developing these maps is a huge undertaking-one that's enjoying a massive investment of money and talent. From a Blip to a Boom Automotive radar rides the 77-GHz technology wave toward greater capability and vehicle safety.

Editorial Trust, testing and transition SAE Standards News SAE updates J3016 automated-driving graphic View from a Visionary Chris Urmson helped give birth to vehicle autonomy. His company, Aurora, is leading the technology to maturity and widespread adoption. Extending EV Range Using AV Programming Intelligent programming of autonomous electric vehicles offers potentially big energy savings, according to a study by IAV. Intel Study: Autonomous Vehicles Expected to be Common-in 50 Years New U.S. consumer survey sees most Americans "expect" AVs, though many currently fear the technology. Europe's Latest AV Testing Facilities Key for Swift Autonomous Adoption The need for data sharing and commonality in burgeoning AV technologies is bringing new meaning to the words 'proving grounds.' End Public 'Shadow' Driving! The best way to test and train AI for autonomous vehicles is through proper simulation, systems engineering, and an end-state scenario matrix.

The Autonomous Vehicle QuickStart Primer by Dr. Rahul Razdan is valuable for anyone connected to the transportation industry who wants a basic understanding of the impact of the new wave of electronics and software technology that’s about to transform this world. The book is aimed at professionals who seek insights into the fundamentals of AV technology, business, and regulation, but it doesn’t cover deep engineering and is not highly technical. Instead, it offers a firm foundation of the megatrends driving this technological revolution, the way these technologies intersect with the current transportation system, and the potential for disruptive change. The book takes a look at challenges in the areas of public policy, regulations, safety, legal, and insurance frameworks that are currently being debated, and the pilot programs being implemented in some areas.