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., 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.

Do you know what personal protective equipment (PPE), tools, and instruments are needed to keep you safe around high voltage (HV) vehicles? Are you aware of how to protect yourself or your employees when working around high voltage systems and platforms? Safety is paramount when working around any type of high voltage. As electric vehicles (EV) and EV fleets become more prevalent, the critical need for OEMs, suppliers, companies, and organizations to provide comprehensive safety training for teams working with or around xEV systems and platforms increases.

From hydrogen-fueled buses to AI-driven advancements and cybersecurity, this book offers an unparalleled glimpse into the future of transit. Navigate the complexities of transit planning in a post-COVID world, where innovative solutions are essential to tackle infrastructure challenges and workforce shortages.

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.

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.

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.

Looking past ADAS Advances in perception hardware and software deliver new performance possibilities - and a refreshed vision for passenger-vehicle driving automation. Provizio eyes safety with radar, not lidar Provizio promises its 5D Perception stack can safely compete with expensive lidar sensors at a fraction of the cost. Can solid-state batteries commercialize by 2030? Solid-state batteries are facing a reckoning as OEMs attempt to commercialize the technology. Editorial Change?

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.

Cybersecurity of high-power charging infrastructure for electric vehicles (EVs) is critical to the safety, reliability, and consumer confidence in this publicly accessible technology. ...Cybersecurity of high-power charging infrastructure for electric vehicles (EVs) is critical to the safety, reliability, and consumer confidence in this publicly accessible technology. Cybersecurity vulnerabilities in high-power EV charging infrastructure may also present risks to broader transportation and energy-infrastructure systems. ...This paper details a methodology used to analyze and prioritize high-consequence events that could result from cybersecurity sabotage to high-power charging infrastructure. The highest prioritized events are evaluated under laboratory conditions for the severity of impact and the complexity of cybersecurity manipulation.

Cybersecurity (CS) is crucial and significantly important in every product that is connected to the network/internet. ...Hence making it very important to guarantee that every single connected device shall have cybersecurity measures implemented to ensure the safety of the entire system. Looking into the forecasted worldwide growth in the electric vehicles (EV’s) segment, CS researchers have recently identified several vulnerabilities that exist in EV’s, electric vehicle supply equipment (EVSE) devices, communications to EVs, and upstream services, such as EVSE vendor cloud services, third party systems, and grid operators. ...Additional processes have been defined in the process reference and assessment model for the CS engineering in order to incorporate the cybersecurity related processes in the ASPICE scope. This paper aims at providing a model & brief overview to establish a correlation between the ASPICE, ISO/SAE 21434 and the ISO 26262 functional safety (FS) standards for development of a secured cybersecurity software with all the considerations that an organization can undertake.

SMSOLUTIONS0123 represents the work of a team of policy and technical leaders from over a dozen forward-leaning organizations in the ground vehicle industry and government. When asked where Sustainable Mobility Solutions could best apply the capabilities SAE has developed over a century, the SMS group responded without hesitation: address EV charging system failure. The group determined to aggregate charging session data with the view to create a consistent data dictionary and analysis practice. Adopting agile work practices, it studied these data, vetting and iterating its solution with the objective of producing a technical report in approximately half the time required in normal standardization. The resulting document, EV Charging Infrastructure: Charging System Performance Reporting, is informing work by the U.S. Department of Energy and Departments of Energy and Transportation Joint Office, as well as OEMs and suppliers.

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.

Impact of Electric Vehicle Charging on Grid Energy Buffering discusses the unsettled issues and requirements needed to realize the potential of EV batteries for demand response and grid services, such as improved battery management, control strategies, and enhanced cybersecurity. Hybrid and fuel cell EVs have significant potential to act as “peakers” for longer duration buffering, and this approach has the potential to provide all the long-term energy buffering required by a VRE-intensive grid.

Abstract Vehicular communications face unique security issues in wireless communications. While new vehicles are equipped with a large set of communication technologies, product life cycles are long and software updates are not widespread. The result is a host of outdated and unpatched technologies being used on the street. This has especially severe security impacts because autonomous vehicles are pushing into the market, which will rely, at least partly, on the integrity of the provided information. We provide an overview of the currently deployed communication systems and their security weaknesses and features to collect and compare widely used security mechanisms. In this survey, we focus on technologies that work in an ad hoc manner. This includes Long-Term Evolution mode 4 (LTE-PC5), Wireless Access in Vehicular Environments (WAVE), Intelligent Transportation Systems at 5 Gigahertz (ITS-G5), and Bluetooth.

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.

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.

The project uses PKI to help protect the connection between EVs and charging stations.

An eye-opening Q&A with an impressive panel of experts lays out terrifying cyberattack scenarios including weaponizing EVs and region-wide blackouts.

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.

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.