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COMVEC™ conference is the only North American event that addresses vehicles and equipment spanning on-highway, off-highway, agricultural, construction, industrial, military, and mining sectors.

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.

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.

Abstract Secure boot is a fundamental security primitive for establishing trust in computer systems. For real-time safety applications, the time taken to perform the boot measurement conflicts with the need for near instant availability. To speed up the boot measurement while establishing an acceptable degree of trust, we propose a dual-phase secure boot algorithm that balances the strong requirement for data tamper detection with the strong requirement for real-time availability. A probabilistic boot measurement is executed in the first phase to allow the system to be quickly booted. This is followed by a full boot measurement to verify the first-phase results and generate the new sampled space for the next boot cycle. The dual-phase approach allows the system to be operational within a fraction of the time needed for a full boot measurement while producing a high detection probability of data tampering.

DoD to Deploy Thousands of Low Cost Autonomous Systems Under Replicator Program Top Productivity Improvement Tips for Manufacturing Turbine Discs FACE Technical Standard Offers MOSA Lessons for Safety-Critical Software in Any Sector Adamant: A Soon-to-be Open Source, Mission-Critical Flight Software Framework Written in Ada Benefits and Challenges of Direct-RF Sampling for Avionic Platforms More Airports Test RF as Counter Measure for UAS in Restricted Airspace Adapting U.S. Army Acquisition to Ensure the Reliability and Safety of Autonomous Vehicles This report presents several challenges that the U.S. Army will face in the transition to autonomous vehicles, challenges that are only magnified in the current acquisition environment with limited testing. Artificial intelligence algorithms introduce additional complexity, resulting in systems with a complex combination of human, machine, and autonomous controllers.

Fast-track propulsion testing Whether it is compressor refinement or complete test programs for next-generation aircraft, the level of propulsion system development in Europe seems to be ever-increasing.

GM's CTO driving new paths to technology leadership 'We're making actual production commitments regarding our advanced-technology strategy, rather than just talking about it,' says GM's CTO Jon Lauckner. 'We're absolutely going to be among the leaders, if not the leader, in these areas.' Aluminum prepares for its next big leap Ford's F-Series blockbuster was just the beginning. New micromills now in pilot phase aim to bring vastly stronger and more formable light-alloy materials at higher capacity, says Alcoa's Mike Murphy. Slick solutions for friction reduction From new lubricants to 'smart' oil pumps and clever bearing technologies, engine designers are attacking every potential source of spin losses and internal friction in the quest for more mechanical work out of less fuel. Next-gen NSX: a twin-turbo, multi-material Ferrari-fighter The production NSX made its much-awaited global debut at NAIAS in January.

Global Viewpoints The latest strategies are investigated for vehicle development by automakers and major suppliers. Sports cars embrace array of green technology IMSA Tudor United SportsCar Championship promotes a variety of green technologies to link racing to the road. More gears, more challenges Many strategies, as well as key software and hardware aspects related to controllers, networks, sensors, and actuators, must be considered to keep automatic transmissions shifting smoothly as more gears are added to improve fuel economy. Advancing structural composites Industry experts address the opportunities and challenges involved with moving toward composite-intensive vehicles, including Nissan's effort to produce a high-volume, fully recyclable composite liftgate with low metal content.

Volkswagen reveals its 'people's' EV VW's ID.4 leads the 2021 stampede to electrification for the mass market. Answering the fuel-cell compressor question The optimum compressor device for a fuel cell depends on vehicle application - and a lot more. An Eaton expert explains. Tire pressure's impact on EV driving range A new study shows that tighter control of tire-pressure loss can lead to marked improvement in electric-vehicle efficiency. Editorial Warm socks for the EV options list Supplier Eye For suppliers, a new drumbeat New SAE wireless charging standard is EV game-changer Tula DMD aims for more-efficient e-machines Multiphysics helps transform modeling, simulation Is the camshaft being timed out? New Magna seat puts connectivity in the second row BMW reveals its first "M" performance-badged two-wheeler Volkswagen readies new-generation Golf R Q&A Discussing safety tech, standards and industry trends with Hyundai North America's Brian Latouf

New vision @ Gentex Creating a vital ADAS partner through home-grown R&D and manufacturing in (of all places) western Michigan. Positioning for hybrid growth BorgWarner "modularizes" to provide OEMs optimal electrified-driveline flexibility. Editorial: Beleaguered diesel could use a break-or a breakthrough SAE Standards News Kickoff to begin testing program to validate SAE J2954 wireless charging Recommended Practice Supplier Eye Will you be an active participant or passive bystander? The Navigator For future vehicles, communication equals trust Tenneco readies new semi-active digital suspension for 2020 New 90-degree turbo V6 leads Audi's hybridization blitz GKN using modular control algorithms for added systems integration U of M students engineer new autonomous shuttle system Jaguar's 2018 E-Pace shares Land Rover bones Ford pumps powertrains for 2018 F-150 2018 Subaru Crosstrek moves to new global platform Nissan's Ponz Pandikithura on EV lifecycle value

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?

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.

In this paper, we outline past, present and future applications of automotive security for engine ECUs. Electronic immobilizers and anti-tuning countermeasures have been used for several years. Recently, OEMs and suppliers are facing more and more powerful attackers, and as a result, have introduced stronger countermeasures based on hardware security. Finally, with the advent of connected cars, it is expected that many things that currently require a physical connection will be done remotely in a near future. This includes remote diagnostics, reprogramming and engine calibration.

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.

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.

Automotive electronics and enterprise IT are converging and thus open the doors for advanced hacking. With their immediate safety impact, cyberattacks on such systems will endanger passengers. Today, there are various methods of security verification and validation in the automotive industry. However, we realize that vulnerability detection is incomplete and inefficient with classic security testing. In this article, we show how an enhanced Grey-Box Penetration Test (GBPT) needs less test cases while being more effective in terms of coverage and indicating less false positives.

Abstract In this work, we present an approach to support penetration tests by combining safety and security analyses to enhance automotive security testing. Our approach includes a new way to combine safety and threat analyses to derive possible test cases. We reuse outcomes of a performed safety analysis as the input for a threat analysis. We show systematically how to derive test cases, and we present the applicability of our approach by deriving and performing test cases for a penetration test of an automotive electronic control unit (ECU). Therefore, we selected an airbag control unit due to its safety-critical functionality. During the penetration test, the selected control unit was installed on a test bench, and we were able to successfully exploit a discovered vulnerability, causing the detonation of airbags.

CAN bus network proved to be efficient and dynamic for small compact cars as well as heavy-duty vehicles (HDV). However, HDVs are more susceptible to malicious attacks due to lack of security in their intra-vehicle communication protocols. SAE proposed a new standard named J1939-91C for CAN-FD networks which provides methods for establishing trust and securing mutual messages with optional encryption. J1939-91C ensures message authenticity, integrity, and confidentiality by implementing complex cryptographic operations including hash functions and random key generation. In this paper, the three main phases of J1939-91C, i.e., Network Formation, Rekeying, and Message Exchange, are simulated and tested on Electronic Control Units (ECUs) supporting CAN-FD network. Numerous test vectors were generated and validated to support SAE J1939-91C. The mentioned vectors were produced by simulating different encryption and hashing algorithms with variable message and key lengths.