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Announcements for SAE Mobilus

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Important Update – Accessibility Enhancements on SAE Mobilus
We’re pleased to share that SAE Mobilus has recently completed a comprehensive set of accessibility improvements across the platform. As a result, Mobilus is now aligned with WCAG 2.2 Level AA standards in most key categories. These updates are part of our ongoing commitment to ensuring the platform is accessible to all users. Enhancements include improvements to keyboard navigation, screen reader compatibility, visual contrast, error handling, and overall usability across core areas of the site. An updated Voluntary Product Accessibility Template (VPAT v2.5 – March 2026) is now available, providing a detailed overview of our accessibility conformance. You can access the VPAT directly within the Help section. Accessibility is a continuous effort. We will continue to evaluate and improve the platform to better support all users and meet evolving standards. If you have any feedback or experience any accessibility issues, we welcome your input. - The SAE Mobilus Team
SAE AI Chat — Update and What's Next
* Important Update - SAE AI chatbot Beta program * The SAE AI Chatbot Beta program - Phase 1 will end on March 31, 2026. Following this date, the AI chatbot capabilities will be temporarily unavailable as we begin development of a significantly enhanced version. We sincerely thank all Phase 1 Beta participants for their engagement and valuable feedback - your insights have played an important role in shaping the next phase of this experience. The upcoming version of the SAE AI Chatbot will expand content coverage beyond current standards, incorporating additional critical resources from our digital library. It will also be made available to a broader audience across Mobilus. Want to be part of what's next? Register your interest here to receive updates and be considered for early access. For additional information, visit the FAQs. — The Mobilus Team
SAE International Digitization and AI Policy
SAE International prohibits the entry of SAE Content into any form of Artificial Intelligence (AI) tools, such as ChatGPT, OpenAI, or Microsoft Copilot. Additionally, creating derivatives of SAE Content using AI is also prohibited without express written permission from SAE International. In the case of such use, SAE International will suspend access to SAE Content, and further legal action will be considered.
Welcome to the new SAE Mobilus®
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Recent SAE Edge™ Research Reports

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Wing-in-Ground Effect Vehicles: From Modern Military and Commercial Development to Global Disaster ResponseEPR202501711/24/2025
The wing-in-ground effect (WIG) vehicle represents a significant advancement in aerodynamics and vehicle design, leveraging the ground effect phenomenon to enhance lift and reduce drag when flying close to the surface. This unique capability allows WIG vehicles to achieve higher payloads, longer range, and greater fuel efficiency compared to traditional aircraft, making them an attractive option for modern military and global disaster response applications. Wing-in-Ground Effect Vehicles: From Modern Military and Commercial Development to Global Disaster Response discusses future disaster response, logistics, and military applications for WIG vehicles, including the ongoing development of aerospace and transportation technology. Relavant advancements in materials and propulsion systems holds promise for further enhancing WIG performance and operational range. Additionally, cost-effective and powerful flight computers with various types of mission-enabling sensor suites from the
Next-gen AI for Aerospace EngineeringEPR20250169/22/2025
Despite growing investments, the widespread adoption and scalable deployment of generative artificial intelligence (AI) remains a challenge due to data trustworthiness, regulatory uncertainty, interpretability, and ethical governance. The need to accelerate automation and maintain the human-in-the-loop demonstrates broader questions of responsibility and transparency. Next-gen AI for Aerospace Engineering investigates the transformative role of GenAI within aerospace engineering, examining its shift from conventional workflows toward more AI-driven solutions in design, manufacturing, and maintenance. It emphasizes GenAI’s emerging ability to automate repetitive mundane tasks, reduce design complexity, and optimize engineering pipelines. The report underscores the need for validation methods that must align AI-generated outputs with physics-informed models, integration with legacy engineering tools (e.g., computational fluid dynamics, finite element analysis, digital twins), and
Sustainable Circular Future Mobility: Environmental Impact of Next-gen VehiclesEPR20250159/22/2025
The next generation of mobility, driven by shared, driverless, connected, and electrified vehicles, holds strong potential to advance sustainability through lower emissions and improved resource efficiency. However, critical questions remain regarding their true environmental impact, including battery lifecycle management, material consumption, and circular manufacturing practices. Sustainable Circular Future Mobility: Environmental Impact of Next-gen Vehicles explores these unresolved issues, focusing on the shift from internal combustion to electric vehicles, supply chain challenges, regulatory gaps, and the operational realities of sustainable productization. It also critically examines the risks of greenwashing, the need for consistent standards, and the role of intersectoral collaboration—with energy, urban planning, information and communications technologies, and waste management sectors—in building resilient, scalable solutions. The report provides strategic recommendations and
Small, Mobile, and Autonomous Agricultural RobotsEPR20250128/13/2025
The automation of labor-intensive picking and planting operations is having an immediate impact in the agricultural indutry. In its simplest form, robotic automation can reduce the labor and soil disturbance while enabling organic soil cover and increasing species diversification through precision approaches to planting, weeding, and spraying. With this, pesticides and fertilizers can be applied in a more targeted way, and with machinery visiting fields more frequently, earlier and more targeted intervention can occur before pests become established. Small, Mobile, and Autonomous Agricultural Robots identifies issues that need to be resolved fo for this technology to thrive, including improving methods of acquiring and labeling training data to facilitate more accurate models for specific applications. It also discusses concepts such as general-purpose mechanical platforms for use as carriers of agricultural automation systems with high stability, positional accuracy, and variable
Safety Impacts of Active Safety and Driving Automation FeaturesEPR20250138/13/2025
Advanced technologies that assist the human driver or reduce (or even eliminate) the human driver’s role are becoming increasingly prevalent in new light-duty vehicles used by the general public. These technologies are divided between Active Safety features that monitor the human driver and vehicle motion and act intermittently to mitigate and avoid crashes, and Driving Automation features that assume some or all of the dynamic driving task from the human driver. Both types of technologies have the potential to reduce injuries and save lives by reducing the frequency and/or severity of crashes. Safety Impacts of Active Safety and Driving Automation Features addresses the current capabilities and future potential for Active Safety and Driving Automation features to reduce crash frequency and severity and provides an overview of the state of the industry for both types of features, including current deployments, trends, and anticipated rollouts. Gaps in knowledge, unsettled issues, and
Hybrid Data- and Physical Model-driven Safe and Intelligent Motion Planning and Control for Autonomous VehiclesEPR20250147/18/2025
Autonomous vehicle motion planning and control are vital components of next-generation intelligent transportation systems. Recent advances in both data- and physical model-driven methods have improved driving performance, yet current technologies still fall short of achieving human-level driving in complex, dynamic traffic scenarios. Key challenges include developing safe, efficient, and human-like motion planning strategies that can adapt to unpredictable environments. Data-driven approaches leverage deep neural networks to learn from extensive datasets, offering promising avenues for intelligent decision-making. However, these methods face issues such as covariate shift in imitation learning and difficulties in designing robust reward functions. In contrast, conventional physical model-driven techniques use rigorous mathematical formulations to generate optimal trajectories and handle dynamic constraints. Hybrid Data- and Physical Model-Driven Safe and Intelligent Motion Planning and
Product Assurance in the Age of Artificial IntelligenceEPR20250115/21/2025
Driven by the vast consumer marketplace, the electronics megatrend has reshaped nearly every sector of society. The advancements in semiconductors and software, originally built to serve consumer demand, are now delivering significant value to non-consumer industries. Today, electronics are making inroads into traditionally conservative, safety-critical sectors such as automotive and aerospace. In doing so, electronics—now further propelled by artificial intelligence—are disrupting the functional safety architectures of these cyber-physical systems. Electronics have created the world of cyber-physical systems, raising broader concerns about the broader category of product assurance. Product Assurance in the Age of Artificial Intelligence continues the work of previous SAE Edge Research Reports in examining open research challenges arising from this shift, particularly in automotive systems, as core electronic technologies (e.g., the combination of software and communications) have even
Edge Artificial Intelligence in Connected, Cooperative and Automated MobilityEPR20250095/20/2025
With many stakeholders involved, and major investments supporting it, the advancements in automated driving (AD) are undoubtedly there. Generally speaking, the motivation for advancing AD is driver convenience and road safety. Regarding the development of AD, original equipment manufacturers, technology start-ups, and AD systems developers have taken different approaches for automated vehicles (AVs). Some manufacturers are on the path toward stand-alone vehicles, mostly relying on onboard sensors and intelligence. On the other hand, the connected, cooperative, and automated mobility (CCAM) approach relies on additional communication and information exchange to ensure safe and secure operation. CCAM holds great potential to improve traffic management, road safety, equity, and convenience. In both approaches, there are increasingly large amounts of data generated and used for AD functions in perception, situational awareness, path prediction, and decision-making. The use of artificial
Leveraging Advanced Data Technologies for Smart Traffic ManagementEPR20250085/20/2025
The transportation industry is transforming with the integration of advanced data technologies, edge devices, and artificial intelligence (AI). Intelligent transportation systems (ITS) are pivotal in optimizing traffic flow and safety. Central to this are transportation management centers, which manage transportation systems, traffic flow, and incident responses. Leveraging Advanced Data Technologies for Smart Traffic Management explores emerging trends in transportation data, focusing on data collection, aggregation, and sharing. Effective data management, AI application, and secure data sharing are crucial for optimizing operations. Integrating edge devices with existing systems presents challenges impacting security, cost, and efficiency. Ultimately, AI in transportation offers significant opportunities to predict and manage traffic conditions. AI-driven tools analyze historical data and current conditions to forecast future events. The importance of multidisciplinary approaches and
Space-based Solar Power for Instantaneously Dispatchable Renewable Power on EarthEPR20250054/24/2025
Recent advances are reducing the cost of space launch, high specific power solar cells, and the production of satellite systems. Modular architectures with no moving parts and distributed power systems would minimize assembly and maintenance costs. Together, this may enable space-based solar power to provide decarbonized dispatchable power at a lower cost than equivalent technologies such as nuclear power stations. Space-based Solar Power for Instantaneously Dispatchable Renewable Power on Earth discusses the advances in emerging technologies, like thin film solar cells, reusable launch vehicles, and mass-produced modular satellite systems that would make economic space power feasible. Click here to access the full SAE EDGETM Research Report portfolio.

Latest Journal Issues

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Passenger Vehicle Systems
SAE International Journal of Passenger Vehicle Systems
Electrified Vehicles
SAE International Journal of Electrified Vehicles
Advances and Current Practices in Mobility
SAE International Journal of Advances and Current Practices in Mobility
Sustainable Transportation, Energy, Environment, & Policy
SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy
Connected and Automated Vehicles
SAE International Journal of Connected and Automated Vehicles
Transportation Cybersecurity and Privacy
SAE International Journal of Transportation Cybersecurity and Privacy
Vehicle Dynamics, Stability, and NVH
SAE International Journal of Vehicle Dynamics, Stability, and NVH
Transportation Safety
SAE International Journal of Transportation Safety
Alternative Powertrains
SAE International Journal of Alternative Powertrains
Commercial Vehicles
SAE International Journal of Commercial Vehicles
Materials and Manufacturing
SAE International Journal of Materials and Manufacturing
Engines
SAE International Journal of Engines
Fuels and Lubricants
SAE International Journal of Fuels and Lubricants
Aerospace
SAE International Journal of Aerospace
Passenger Cars - Mechanical Systems
SAE International Journal of Passenger Cars - Mechanical Systems

Recent Books

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Aerospace Standards Index - 2026ASIN20262/25/2026
This valuable resource lists all Aerospace Standards (AS), Aerospace Recommended Practices (ARP), Aerospace Information Reports (AIR), and Aerospace Resource Documents (ARD) published by SAE. Each listing includes title, subject, document number, key words, new and revised documents, and DODISS-adopted documents. AMS Index - Now Available!
Business Reliability Growth for Automotive Engineering, Volume 4R-5522/17/2026
In a world where every business process is under pressure to perform faster, safer, and more reliably, this book delivers a powerful roadmap for sustained operational excellence. Centered on the proven methodology of Design of Experiments (DOE), it shows how organizations can move beyond reactive problem-solving to systematic reliability growth. From well-defined standard operating practices to management-level decision-making, the book connects strategy, data, and execution to create repeatable, measurable results across the enterprise. Readers are guided through practical, real-world applications of DOE, from selecting the right factors and levels to executing robust experiments, analyzing outcomes, validating solutions, and continuously monitoring performance. Each chapter translates complex statistical and engineering concepts into actionable business value, helping teams improve quality, reduce waste, and increase return on investment. Key capabilities explored in this book
January 2026 AMS IndexAMSJAN-20261/24/2026
Fundamentals of Sustainable Aviation FuelsR-5471/22/2026
As global energy demands rise and environmental challenges intensify, the aviation industry faces a critical need to redefine how it powers the skies. Fundamentals of Sustainable Aviation Fuels presents a comprehensive, research-driven exploration of the transition from fossil-based fuels to renewable alternatives that promise to reshape the future of air transportation. This book bridges the gap between academic knowledge and industrial application, offering a detailed overview of the science, technology, and policy driving the adoption of Sustainable Aviation Fuels (SAFs). From understanding feedstocks and conversion pathways to evaluating production technologies, emissions performance, and life-cycle impacts, the text equips readers with a holistic understanding of SAFs within today’s global energy landscape. Across five insightful chapters, readers will find a clear roadmap: the evolution and importance of SAFs; production methods and technological foundations; environmental
SAE International’s Dictionary of ADAS and Connected VehiclesR-5591/20/2026
The convergence of Advanced Driver Assistance Systems (ADAS) and connected vehicle technologies is ushering in a transformative era of automotive innovation—one that is fundamentally enhancing vehicle safety, efficiency, reliability, and the overall driving experience. SAE International’s Dictionary of ADAS and Connected Vehicles stands as the definitive reference for this rapidly evolving domain, meticulously compiled to clarify and standardize the language shaping modern mobility. Inside, readers will find clear, authoritative definitions encompassing the full spectrum of technologies that enable connected and automated driving—including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-everything (V2X) communication systems. This comprehensive resource translates complex engineering terminology into accessible language, enabling engineers, researchers, policymakers, educators, and enthusiasts to share a common technical foundation. Reflecting the latest
Electrification: Vol. 3EPRCOMPV04202512/29/2025
Safety, ADAS, and Cybersecurity: Vol. 4EPRCOMPV01202512/29/2025
Infrastructure Enablers for Automation: Vol. 4EPRCOMPV02202512/29/2025
Automated Vehicles: Development, Testing, and Validation: Vol. 4EPRCOMPV03202512/29/2025
Commercial Vehicles: Vol. 2EPRCOMPV05202512/29/2025

Recently Published

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Steel Bars, Forgings, and Tubing, Nitriding, 1.4Cr - 1.2Mo - 0.3V (0.29 - 0.36C), (32CrMoNiV5), Double Vacuum Melted, Premium Aircraft-Quality for Bearing ApplicationsAMS6498C (Current)4/9/2026
This specification covers a nitriding grade of premium aircraft-quality, low-alloy steel in the form of bars, forgings, mechanical tubing, and forging stock. AMS6496 and AMS6497 cover UNS K23280 with other quality levels.
AMS E Carbon and Low Alloy Steels Committee
Magnesium Alloy, Investment Castings, 8.7Al - 0.70Zn - 0.22Mn (AZ91C-T6), Solution and Precipitation Heat TreatedAMS4452G (Current)4/9/2026
This specification covers a magnesium alloy in the form of investment castings (see 8.6).
AMS D Nonferrous Alloys Committee
Aluminum Alloy, Rolled or Forged Rings, 5.6Zn - 2.5Mg - 1.6Cu - 0.23Cr (7075-T651, 7075-T652), Solution Heat Treated, Mechanically Stress Relieved, and Precipitation Heat TreatedAMS4310G (Current)4/9/2026
This specification covers an aluminum alloy in the form of rolled or forged rings up to 6 inches (152 mm), inclusive, in thickness (see 3.3.1.1.1) and an OD to wall thickness ratio of 10 or greater (see 8.5).
AMS D Nonferrous Alloys Committee
Thermal Management of Electric Microtruck Motors2026-01-50264/9/2026
This study investigates the gradeability performance of an L7e-class electric micro truck from both vehicle dynamics and thermal perspectives. A 1D simulation model (Amesim) was developed and validated with multiple test results. Using inputs such as motor characteristics, drivetrain configuration, and vehicle mass, the model analyzed vehicle performance on a 20% gradient, calculating the required torque, achievable motor speed, and corresponding vehicle speed. Furthermore, gradeability limits were evaluated, and the effects of gear ratio and airflow rate around the air-cooled motor on both gradeability and thermal behavior were examined. The findings provide practical insights for improving the powertrain and cooling system design of lightweight electric vehicles. The results showed that selecting an appropriate gear ratio can enable the motor to operate more efficiently under demanding driving conditions. A 20% increase in the gear ratio was found to delay motor heating by up to 10
Turan, Azim, Kantaroğlu, Hasan Hüseyin, Akbaba, Mahir, Kasım, Recep Faruk, Yarar, Göktuğ
Assessing Injury Prediction with Human Body Models: Application to Rib Fracture Risk Prediction Using SAFER HBM09-14-01-00234/8/2026
As a consequence of the introduction of mathematical human body models (HBMs) in consumer information programs, there is an increased need for reliable methods that can demonstrate and build trust in the capability of HBMs to predict human response and injury risk in crashes. Therefore, a framework for validation of strain-based injury prediction is proposed. The framework comprises stepwise validation with the final step to validate the utility of risk predictions by means of the area under the curve (AUC) combined with Brier scores. SAFER HBM V11.1.0 previously validated at component and body part levels was selected for the demonstration of the final step of the framework to validate the capability to predict fracture risk in frontal, oblique, and lateral loading. For frontal loading, five postmortem human surrogate (PMHS) test series with 43 PMHS (age range: 19–88 years) were reconstructed. The predicted rib fracture risk for 2+ and 3+ fractured ribs was compared to the number of
Pipkorn, Bengt, Niranjan Poojary, Yash, Osth, Jonas, Larsson, Karl-Johan, Iraeus, Johan
Test Method for Measuring Wet Color Transfer CharacteristicsJ1326_202604 (Current)4/8/2026
This procedure describes a method of measuring the resistance to wet color transfer of materials such as textiles, leather, and composites.
Textile and Flexible Plastics Committee
Integration and Certification Considerations for Electrified Propulsion AircraftAIR7128 (Current)4/8/2026
This document provides a comprehensive compilation of currently available practices, standards, regulations, and guidance material that have been considered relevant for developing an electrified propulsion system (independently or as part of an aircraft) and that may also help the applicants in the process of building their own certification approach with their Authority. It also covers unique considerations for electrified propulsion development and aircraft integration. It focuses on the particularities introduced by the new technology. This document is not intended to represent a proposed Means of Compliance (MoC) with any particular certification regulation.
E-40 Electrified Propulsion Committee
STUD, LOCKED-IN RING, SERRATED, HIGH STRENGTHAS51992D (Current)4/8/2026
E-25 General Standards for Aerospace and Propulsion Systems
Measurement Procedures for Short Pulse Width Strobe Anticollision LightsARP5029C (Current)4/8/2026
This SAE Aerospace Recommended Practice (ARP) provides the user with standardized guidelines for the measurement of effective intensity of short pulse width strobe anticollision lights for aircraft in the laboratory, in maintenance facilities, and in the field. A common source of traceability for calibration of the measurement systems, compensation for known causes of variation in light output such as the use of colored lenses, and recommendations which minimize sources of errors and uncertainties are included in this document. Estimates of uncertainty and error sources for each class of measurement are discussed.
A-20B Exterior Lighting Committee
Magnesium Alloy, Investment Castings, 9.0Al - 2.0Zn (AZ92A-T6), Solution and Precipitation Heat TreatedAMS4453H (Current)4/8/2026
This specification covers a magnesium alloy in the form of investment castings (see 8.6).
AMS D Nonferrous Alloys Committee
Sampling, Conformance Strategies, and Recommended Practices for Closed Loop Processing of Powder for Additive ManufacturingARP7302 (Current)4/8/2026
This SAE Aerospace Recommended Practice (ARP) establishes methods and identifies opportunities to sample used powder feedstock circulating within closed loop equipment of an additive manufacturing (AM) process for the purpose of showing conformance to a powder specification. Powder within the entirety of closed loop equipment cannot be represented by sampling and testing of discrete, in-process lots. Because powder processing (i.e., reconditioning, conveyance, and storage) is asynchronous with a build cycle, individual samples and their associated tests do not represent the totality of powder committed to a machine. Powder consumed as part of an individual build cycle may only represent a subset of feedstock in circulation within such equipment. Therefore, regular testing to substantiate conformance to a powder specification is required to assert conforming feedstock was consumed during individual build cycles of the AM workflow to fabricate parts or preforms. Operation of some
AMS AM Additive Manufacturing Metals
Copper Alloy (Brass), Sheet, Strip, and Plate, 70Cu - 30Zn, Half Hard (H02)AMS4507K (Current)4/8/2026
This specification covers a copper-zinc alloy (brass) in the form of sheet, strip, and plate (see 8.6).
AMS D Nonferrous Alloys Committee
Aluminum Alloy, Sheet, 3.2Cu - 0.52Mg - 0.30Ag - 0.95 Li - 0.12Zr (2198-T8), Solution Heat Treated, Cold Worked, and Artificially AgedAMS4412C (Current)4/8/2026
This specification covers an aluminum alloy in the form of sheet from 0.063 to 0.249 inch (1.60 to 6.30 mm) in nominal thickness (see 8.6).
AMS D Nonferrous Alloys Committee
Steel, Sheet, Strip, and Plate, 0.75Si - 0.62Cr - 0.20Mo - 0.10Zr (0.10 - 0.17C) (NAX 9115-AC)AMS6354H (Current)4/8/2026
This specification covers a low-alloy steel in the form of sheet, strip, and plate 4.00 inches (101.6 mm) and under in thickness.
AMS E Carbon and Low Alloy Steels Committee
Passenger Vehicle Windshield Demisting and Defrosting SystemsJ902_202604 (Current)4/8/2026
This SAE Recommend Practice establishes for passenger cars, light trucks, and multipurpose vehicles with GVW of 4500 kg (10000 pounds) or less, as defined by the EPA, and M1 category vehicles, as defined by the European Commission:
Interior Climate Control Vehicle OEM Committee
Increasing the Competency and Confidence of Older Drivers in the Use of Advanced Vehicle Technologies: The MOVETech Randomized Controlled Trial09-14-01-00134/7/2026
Programs that teach older drivers how to confidently and competently use advanced vehicle technologies (AVTs) are limited. The MOVETech study evaluated a training program specifically designed to teach older drivers how to use these technologies. Participants (n = 119) were randomized to the intervention (training program) or control group (brochure). The intervention involved an in-person classroom education session on the use and benefits of AVTs, and an on-road driving session where participants drove along a pre-defined route in a dual-controlled vehicle with instruction on AVT use by a driving instructor. All participants completed in-person and telephone assessments at baseline and 3 months. Driving performance and on-road AVT competence assessments were the primary outcomes. Self-reported driving confidence, competence, and confidence in use of AVT, crashes, citations, and count of vehicle damage were the secondary outcomes. Program fidelity was also evaluated using a checklist
Nguyen, Helen, Ren, Kerrie, Coxon, Kristy, Neville, Nick, O’Donnell, Joan, Cheal, Beth, Brown, Julie, Keay, Lisa
SAE Level 2 ADAS Performance in Specific Crash-Imminent Scenarios09-14-01-00154/7/2026
This research examined the performance of SAE Level 2 (L2) advanced driver assistance systems (ADAS) in crash-imminent scenarios (CIS), with particular attention to how vehicle configuration like body style and powertrain (internal combustion engine, plug-in hybrid, electric vehicle) influences vehicle system performance. The objectives were to (1) identify CIS relevant to L2-equipped vehicles using crash databases and naturalistic driving studies (NDSs), (2) develop scenario-based test procedures and test matrices, and (3) evaluate system and vehicle responses across configurations and conditions. Multiple crash data sources were analyzed, including NHTSA’s Standing General Order dataset of L2-related crashes, the Fatality Analysis Reporting System, the Crash Report Sampling System, and NDS data from the Second Strategic Highway Research Program and the Virginia Tech Transportation Institute L2 NDS. Coded variable analyses from the datasets identified three common CIS: lane and road
Beale, Gregory, Kefauver, Kevin, Venegas, Michael, Li, Eric, Chen, Jay, Huggins, Steven, Guduri, Balachandar, Llaneras, Eddy
Accelerating Electrification through Modular Propulsion: GM’S Strategy for BEV and BET Platforms2026-01-04104/7/2026
General Motors (GM) continues to advance its electrification strategy through the development of scalable Battery Electric Vehicle (BEV) and Battery Electric Truck (BET) platforms. This paper highlights GM’s latest BEV and BET products that leverage shared Drive Unit (DU), Rechargeable Energy Storage System (RESS), and integrated power electronic (IPE) components across multiple vehicle programs. By adopting a modular and commonized propulsion architecture, GM achieves significant benefits in manufacturing efficiency, cost optimization, speed to market, and product flexibility. The shared DU, RESS, and IPE components are engineered to meet diverse performance requirements while maintaining high standards of energy efficiency, thermal management, and durability. This approach enables rapid deployment of electrified solutions across various segments, from passenger vehicles to full-size trucks, without compromising on capability or customer experience. The paper outlines the technical
Liu, Jinming, Sevel, Kris, Anwar, Mohammad, Oury, Andrew, Welchko, Brian, Gagas, Brent
Speed Determination Using Audio Analysis of Dash Camera Video from Commercial Vehicle Tires Frequencies for Vehicle Accident Reconstruction2026-01-05364/7/2026
Prior research has validated a reliable method for determining vehicle speed using audio recorded by cameras mounted in vehicles, specifically for rolling passenger vehicle tires. Passenger vehicle tires produce a frequency component directly correlated to vehicle speed when traveling on concrete roadways. However, prior research has not been conducted on audio for rolling commercial vehicle tires, which differ in construction from passenger vehicle tires. The stiffer Commercial tires produce audio signals on roadway surfaces that passenger vehicles tires did not when tested in the prior study. The current research concluded that commercial vehicle tires rolling on various roadway surfaces also generated a frequency that varied with vehicle speed. The purpose of this study was to outline, test, and confirm the source of the speed-dependent frequency and to develop a validated method for use in forensic applications. A modified version of the passenger vehicle tire equation from prior
Vega, Henry V., Cornetto, Anthony, Ngo, Long Justin, Hatab, Ziad, Hunter, Eric
Forensic Acquisition and Analysis of Unsupported Lexus Infotainment Modules via CMD42 Bypass and Data Carving2026-01-05404/7/2026
Crashes involving passenger vehicles increasingly include vehicles equipped with infotainment systems that are unsupported by commercial vehicle system forensics hardware and software. Examiners facing these systems must overcome challenges in acquiring and analyzing user data, requiring an understanding of both digital forensics principles and the proprietary characteristics of the modules. This paper presents a methodology for acquiring data from previously unsupported Lexus infotainment modules, including techniques to bypass CMD42 security locks on SD cards and extract data. Once acquired, the paper outlines methods for analyzing user data through data carving techniques, enabling recovery of information from binary images even when the full file system cannot be reconstructed. Emphasis is placed on maintaining the integrity of the evidence and validating findings through controlled testing. These validation procedures ensure that the recovered information is both accurate and
Burgess, Shanon
From Algorithm to Engineering Judgment: Navigating Topology Optimization’s Limits in Crash Applications2026-01-01894/7/2026
The non-linear nature of crash scenarios has led to many designs being developed through extensive trial and error based on the intuitions of the design engineer. As such, effectively utilizing topology optimization for crash applications offers opportunities to provide major improvements in cost, weight, and passenger safety. Topology optimization is known for creating stiff, lightweight structures, however its application to crash scenarios must be handled carefully. Compliance minimization, the most common optimization objective, can yield misleading designs that prioritize undesirable qualities when developing structures for crash applications. In this paper, the design process of a passenger seat assembly subject to sequentially applied enforced displacement, and crash deceleration loads is discussed. Due to the conflicting nature of compliance minimization and enforced displacement, the design was split into two types of regions; sacrificial, which are regions manually designed
Orr, Mathew, Shi, Yifan, Lee, Jake, Gray, Savannah, Park, Taeil, Wotten, Erik, LeFrancois, Richard, Huang, Yuhao, Patel, Anuj, Kim, Hansu, Burns, Nicholas, Jalayer, Shayan, Grant, Robert, Kok, Leo, Hansen, Eric, Kim, Il Yong
Energy Efficiency Analysis of U-Haul Truck and Trailer Systems: Impact of Tongue Weight and Load Variations2026-01-04664/7/2026
The demand for improved energy efficiency in real-world vehicle operations continues to grow with technology enhancement. When transporting large cargo loads with passenger pickup trucks and rental trailers, the interaction between vehicle payload, towing configuration, and fuel consumption becomes a key factor in overall system efficiency. Understanding how towing configurations and trailer loading influence fuel consumption and vehicle performance is critical for both consumer guidance and vehicle system design. This study investigates the energy efficiency of U-Haul truck and trailer systems, with a particular focus on the influence of trailer tongue weight. U-Haul truck and trailer simulation models were developed using AVL Vehicle Simulation Model (VSM) software, with an F-350 engine brake-specific fuel consumption (BSFC) map integrated to represent realistic engine performance. Two configurations with equal payload were evaluated: (1) a U-Haul truck alone, and (2) a U-Haul truck
Wang, Gang, Kathadi, Mohammad, Yang, William, Chen, Yan
Inertial Pedal Displacement and Brake Switch Activation in Frontal Crash Events2026-01-05414/7/2026
This paper presents research into the inertial displacement of brake pedals and the subsequent activation of brake light switches during crash events. In certain scenarios, such as multiple-impact crashes or crashes with pre-impact interactions such as curb strikes or sideswipes, inertial forces alone may generate sufficient brake pedal movement to trigger the brake switch, activating the brake lights. Such signals may be recorded by an Event Data Recorder (EDR) or observed by witnesses and incorrectly interpreted as an indication of intentional driver braking. To investigate this phenomenon, HYGE sled tests were performed using brake pedal assemblies and associated components from a Toyota Tacoma pickup truck and a Cadillac DeVille passenger sedan. The assemblies were subjected to acceleration pulses simulating a frontal impact, with high-speed video used to capture brake pedal displacement and brake light activation. The tests demonstrated that inertial loading from a pulse with a
Walker, James, Duran, Amanda, Barnes, Daniel, Osterhout, Aaron, Clayton, Aidan
Electrified Propulsion System Balancing for Light Duty Full Size Truck and Sport Utility Vehicles: A 2026 North American Market Perspective2026-01-04124/7/2026
Achieving the stringent EPA CAFE 2032 standards for light-duty full-size trucks and sport-utility vehicles (SUVs) in North American poses significant challenges. While Battery Electric Vehicles (BEVs) offer a clear path to zero tailpipe emissions, their widespread adoption in this segment faces hurdles including range anxiety, payload/towing capabilities, and traditional truck/SUV use cases. This paper investigates a balanced approach, focusing on optimizing propulsion system design with appropriate hardware content, can effectively meet future fuel economy and emissions standards. This investigation examines advanced BEVs and hybrid electric vehicle architectures, including full hybrids (HEVs), and plug-in hybrids (PHEVs) tailored for full-size trucks and SUVs. Considerations include the optimal sizing of internal combustion engines, electric motors, and battery packs to deliver robust performance while maximizing energy efficiency. This paper analyzes the integration of technologies
Babcock, Dillon, Robinette, Darrell
HaloBus: Edge Computing-Enabled Real-Time Boarding and Exit Detection for Enhanced Transportation Safety Using Lightweight AI2026-01-05554/7/2026
This paper proposes HaloBus, an innovative, edge-computing solution designed to mitigate this risk by detecting student boarding and exiting in real time using lightweight AI based methods. A persistent challenge in elementary school transportation is the issue of missing students after they exit their buses, which disproportionately impacts low-income households. Current safety systems place the burden of implementation on individual households, often requiring independent methods. Common methods include applications on a personal device or a small tracker. However, not everyone can afford these options, and ensuring child safety is a primary concern for parents and caregivers. That is why HaloBus was invented. The system employs YOLOv5us—an Ultralytics-enhanced, anchor-free, split-head architecture that offers a superior accuracy speed trade-off. By providing real-time, on-device alerts, HaloBus enables immediate intervention to prevent a student from being left behind, thereby
Getz, Grayson, Zadeh, Mehrdad, Tan, Teik-Khoon