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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.

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 Army hopes a new streamlined development and procurement process will facilitate aid from the automotive sector to design the next generation of combat vehicles.

Steering Mazda's unique course A chassis engineer at heart, Chairman Seita Kanai challenges his engineers to think differently and embrace the Skyactiv technology that has made Mazda a benchmark. Delphi's multi-domain mindset From tackling the cyber threat to putting 48-volt hybrids with Dynamic Skip-Fire on the road, Engineering VP Mary Gustanski is harnessing a technology powerhouse. The evolving tire-development paradigm Advanced tire-simulation modeling allows tire development to keep pace with accelerated vehicle-development cycles. MEMS the word for next-gen HUDs New high-speed, quad-channel laser diode drivers are designed to beat the LCD and DLP incumbents for next-gen vehicle head-up displays.

Editorial V2Reality Blockchain Unchained! The weird world of cryptocurrency exists because of the intense mathematics of blockchain technology. The mobility sector is looking beyond Bitcoin to put blockchain to work in potentially game-changing ways. Are Blockchain and 'Smart Contracts' the Secure Future? Legal risk and reward of blockchain and smart contracts as a prescription for automotive applications Software Building Blocks for AV Systems Elektrobit's unique software framework is designed to smooth development of automated driving functions. Cyber Security Goes Upstream The first cloud-based solution for connected vehicles was born in Israel and is now pilot testing at global OEMs. Electronic Architectures Get Smart Upgradable, scalable and powerful new architectures will help enable data-hungry connected, autonomous vehicles. Aptiv's VP of Mobility Architecture explains.

Editorial High noon for high-level autonomy The Navigator A fork in the road for the AV business The Electric, Autonomous Revolution Lifts Off Engineering the new generation of electric and hybrid vertical-take-off-and-landing vehicles at Wisk and Elroy Air. New SAE Standard for Automated-Driving Developers Developed in less than a year, SAE's new J3216 standard will impact traffic management, operations and safety for automated mobility. Making Data Logging, Replay and Prototyping More Efficient High levels of continuity and compatibility are vital to avoid interruptions in the development process - and reduce cost. Radar Death Star ELunewave's 3D-printed spherical antenna makes for fast, 360-degree single-snapshot readings that are claimed to beat the slower sweeps of conventional radar. The Case for FOTA in AV Data Security Firmware over-the-air data transmission helps OEMs drive secure vehicle autonomy.

Editorial AV lidar enters a new reality The Navigator UNECE takes first step toward AV regulation Special Delivery - by 'Bot Michigan start-up Refraction AI aims to be the go-to for last-mile, semi-autonomous, all-weather delivery robots. Lidar Infiltrates ADAS Once considered a necessity only in fully autonomous vehicles, lidar sensors are now being evaluated for lower-level driver-assistance systems. Training Data-hungry AI Algorithms Large-scale data refinement is key to bringing more sophisticated automated-driving functions to series production. Simulation's Next Generation Do autonomous-vehicle developers have their simulation strategies all wrong? Some experts think so - but suggest there's a practical solution. Marelli's COVID-killing HVAC Insert With big implications for shared mobility, a new photocatalytic cabin-air purifier claims to kill viruses - including COVID-19. Is Ground-penetrating Radar Next for AV Sensing?

The article also focus on innovative approaches that have recently adopted my many cybersecurity professionals for secured operation of ITS involving block-chain, artificial intelligence, and Machine Learning.

It delivers details on key subject areas including: • SAE International Standard J3061; the cybersecurity guidebook for cyber-physical vehicle systems • The differences between automotive and commercial vehicle cybersecurity. • Forensics for identifying breaches in cybersecurity. • Platooning and fleet implications. • Impacts and importance of secure systems for today and for the future. ...This book provides a thorough view of cybersecurity to encourage those in the commercial vehicle industry to be fully aware and concerned that their fleet and cargo could be at risk to a cyber-attack. ...It delivers details on key subject areas including: • SAE International Standard J3061; the cybersecurity guidebook for cyber-physical vehicle systems • The differences between automotive and commercial vehicle cybersecurity. • Forensics for identifying breaches in cybersecurity. • Platooning and fleet implications. • Impacts and importance of secure systems for today and for the future.

Abstract Testing and verifying the security of connected and autonomous vehicles (CAVs) under cyber-physical attacks is a critical challenge for ensuring their safety and reliability. Proposed in this article is a novel testing framework based on a model of computation that generates scenarios and attacks in a closed-loop manner, while measuring the safety of the unit under testing (UUT), using a verification vector. The framework was applied for testing the performance of two cooperative adaptive cruise control (CACC) controllers under false data injection (FDI) attacks. Serving as the baseline controller is one of a traditional design, while the proposed controller uses a resilient design that combines a model and learning-based algorithm to detect and mitigate FDI attacks in real-time.

., driver assistance functions, intrusion detection system, vehicle diagnostics, external device authentication during vehicle diagnostics, vehicle-to-grid and so on). The cybersecurity attacks targeting the global time result in false time, accuracy degradation, and denial of service as stated in IETF RFC 7384.

In the past, research on blockchain technology has addressed security and privacy concerns within intelligent transportation systems for critical V2I and V2V communications that form the backbone of Internet of Vehicles. Within trucking industry, a recent trend has been observed towards the use of blockchain technology for operations. Industry stakeholders are particularly looking forward to refining status quo contract management and vehicle maintenance processes through blockchains. However, the use of blockchain technology for enhancing vehicle performance in fleets, especially while considering the fact that modern-day intelligent vehicles are prone to cyber security threats, is an area that has attracted less attention. In this paper, we demonstrate a case study that makes use of blockchains to securely optimize the fuel economy of fleets that do package pickup and delivery (P&D) in urban areas.

Autonomous vehicles might one day be able to implement privacy preserving driving patterns which humans may find too difficult to implement. In order to measure the difference between location privacy achieved by humans versus location privacy achieved by autonomous vehicles, this paper measures privacy as trajectory anonymity, as opposed to single location privacy or continuous privacy. This paper evaluates how trajectory privacy for randomized driving patterns could be twice as effective for autonomous vehicles using diverted paths compared to Google Map API generated shortest paths. The result shows vehicles mobility patterns could impact trajectory and location privacy. Moreover, the results show that the proposed metric outperforms both K-anonymity and KDT-anonymity.

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.

The results of this work is allowed to identify a number of cybersecurity threats of the automated security-critical automotive systems, which reduces the efficiency of operation, road safety and system safety. ...According to the evaluating criterion of board electronics, the presence of poorly-protected communication channels, the 75% of the researched modern vehicles do not meet the minimum requirements of cybersecurity due to the danger of external blocking of vital systems. The revealed vulnerabilities of the security-critical automotive systems lead to the necessity of developing methods for mechanical and electronic protection of the modern vehicle. ...The law of normal distribution of the mid-points of the expert evaluation of the cyber-security of a modern vehicle has been determined. Based on the system approach, ranking of the main cybersecurity treats is performed.

Abstract “It cannot happen to us” is one of many common myths regarding cybersecurity in the transportation industry. The traditional view that the threats to transportation are low probability and low impact keep agencies from mitigating security threats to transportation critical infrastructure.

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.

The road to victory is not a straight line Through highs and lows and curves in the road, Milwaukee School of Engineering's Formula SAE Hybrid team kept its focus and ended up with a championship. Winging it BYU-Idaho students develop innovative wing-to-fuselage connection for SAE Aero Design competition. The SpiRIT of Baja BYU-Idaho students develop innovative wing-to-fuselage connection for SAE Aero Design competition. Kettering Baja SAE hoists the SAE Collegiate Cup Seven SAE Collegiate Design Series teams competed in an annual presentation contest hosted by the SAE Mid-Michigan Section.

Abstract Vehicle to Everything (V2X) allows vehicles, pedestrians, and infrastructure to share information for the purpose of preventing accidents, enhancing road safety, and improving the efficiency and energy consumption of transportation. Although V2X messages are authenticated, their content is not validated. Sensor errors or adversarial attacks can cause messages to be perturbed and, therefore, increase the likelihood of traffic jams, compromise the decision process of other vehicles, or provoke fatal crashes. In this article, we introduce V2X Core Anomaly Detection System (VCADS), a system based on the theory presented in [1] and built for the fields provided in the periodic messages shared across vehicles (i.e., Basic Safety Messages, BSMs). VCADS uses physics-based models to constrain the values in each field and detect anomalies by finding the numerical difference between a field and independent derivations of the same field.