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Announcements for SAE Mobilus

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NEW on Mobilus: Try SAE AI Chat (Beta)
Dear patrons, We’re excited to introduce SAE AI Chat – a new AI-powered feature now available in beta on Mobilus. With SAE AI Chat, you can: Ask natural language questions and receive responses derived from 12,000+ SAE standards Save time searching through extensive technical documents Summarize text and discover connections between different topics or publications The feature is currently in beta development phase and may have limitations.   How to Get Access? This beta release is currently available only to a limited number of users. To request access: Visit our Signup Page  Complete the form (< 2 minutes) We'll notify you if you've been selected for the beta program with instructions to login. We'll be rolling out access starting towards end of June 2025, so we encourage you to sign up promptly if you're interested.   Have Questions? Visit the FAQs section or contact us for additional information. - 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®
  Welcome to the new era of SAE Mobilus®, redesigned with a modern, intuitive web interface featuring enhanced search capabilities to help you stay informed and easily discover content. Login today: To access content within your subscription and make the most of the platform, please log into your subscription and your personal My Library (sign up is free) located in the top right corner of the screen.   Key Features Intuitive User Interface: We've listened to our customers and tied this to the best practices in the industry to offer an improved, intuitive, and desirable website experience for our users.​ Improved In-app Discoverability: Enhanced search and expanded menu featuring search suggestions that allow for quick discovery of content.​ Announcements: Stay up to date on new features through a dedicated announcements page. Most recent announcements also get featured on the homepage.​ Enhanced Browse capabilities: Browse through over 200,000 publications that are now classified into categories commonly used across the industry. Deep-dive further into any topic or sub-topic of interest to make the most for your corporate projects or research.​ Smart Automation: "Meta Tags" on each result will help you find content related to your search.​ My Library: My dashboard is rebranded as My Library with powerful features to help you make the most out of the platform Mobile Friendly: Upgraded navigation on mobile devices​ Training Available SAE’s Customer Success team is dedicated to delivering the best platform experience possible. Through monthly trainings and short, on-demand video tutorials, find answers to your questions here: SAE Mobilus Spotlight training - Available monthly, hosted live by SAE’s Customer Success team Mobilus Minute – 2-minute videos, available on-demand   Need some troubleshooting help? Access our FAQs by visiting our Help section: https://saemobilus.sae.org/help/home Resources to help you navigate the new platform are available here, where you can find links to quick start guides and video tutorials on features like My Library, Announcements, Saved Search, Login and new features. Have feedback that you'd like to share with us? Please submit your feedback to the Mobilus team through the blue Knowledge bot in the bottom right hand corner of the new platform.

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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
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
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
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
Automated Vehicles and Infrastructure Enablers: Dedicated LanesEPR20250074/24/2025
Dedicated lanes provide a simpler operating environment for ADS-equipped vehicles than those shared with other roadway users including human drivers, pedestrians, and bicycles. This final report in the Automation and Infrastructure series discusses how and when various types of lanes whether general purpose, managed, or specialty lanes might be temporarily or permanently reserved for ADS-equipped vehicles. Though simulations and economic analysis suggest that widespread use of dedicated lanes will not be warranted until market penetration is much higher, some US states and cities are developing such dedicated lanes now for limited use cases and other countries are planning more extensive deployment of dedicated lanes. Automated Vehicles and Infrastructure: Dedicated Lanes includes a review of practices across the US as well as case studies from the EU and UK, the Near East, Japan, Singapore, and Canada. Click here to access the full SAE EDGETM Research Report portfolio.

Latest Journal Issues

Browse All 16
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
Engines
SAE International Journal of Engines
Materials and Manufacturing
SAE International Journal of Materials and Manufacturing
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
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
Manufacturing and Industry 4.0 : Vol. 2EPRCOMPV06202512/29/2025

Recently Published

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Advanced Tool for Traffic Crash Analysis: An AI-Driven Multi-Agent Approach to Pre-Crash Reconstruction09-14-01-00333/31/2026
Traffic collision reconstruction traditionally relies on human expertise and, when performed properly, can be incredibly accurate. However, attempting to perform pre-crash reconstruction, i.e., reconstructing the driver and vehicle behaviors that preceded the actual crash, poses significantly more challenges. This study develops a multi-agent artificial intelligence (AI) framework that reconstructs pre-crash scenarios and infers vehicle behaviors from fragmented collision data. We present a two-phase collaborative framework combining reconstruction and reasoning phases. The system processes 277 rear-end lead vehicle deceleration (LVD) collisions from the Crash Investigation Sampling System (CISS; 2017–2022), integrating textual crash reports, structured tabular data, and visual scene diagrams. Phase I generates natural language crash reconstructions from multimodal inputs. Phase II performs in-depth crash reasoning by combining these reconstructions with the temporal event data
Xu, Gerui, Chen, Boyou, Guo, Huizhong, LeBlanc, Dave, Kusari, Arpan, Yarbasi, Efe, Ahmed, Ananna, Sun, Zhaonan, Bao, Shan
Assessing the Influence of Reclined Vehicle Seatback Configurations with and without a Belt-Positioning Booster on Child Posture via Pressure Mapping09-14-01-00043/31/2026
Objective: This study sought to implement pressure mapping methodology to assess variation in children’s center of force positions in reclined vehicle scenarios. Methods: Thirty-four children between 4 and 12 y (8.1 ± 2.0 y) were statically evaluated on a vehicle seat across two seating conditions (with and without a backless booster) and three seatback recline conditions (25°, 45°, and 60°). Center of force was recorded using pressure sensors attached to the seating surface. Average center of force fore/aft positions were calculated and transformed into the vehicle coordinate system using 3D coordinate measurements. Descriptive statistics and repeated measures ANOVA were used to assess variation in center of force position across seating and recline conditions, with subject included as a random effect. Results: Center of force fore/aft position varied (p < 0.05) with recline condition, seating condition, and the recline/seating condition interaction term. On the booster, the average
Baker, Gretchen H., Connell, Rosalie R., Graci, Valentina, Mansfield, Julie A.
Advancing Steel Joining: A Critical Review of Adhesives and Sealants for High-Performance Automotive and Construction Applications05-19-04-00253/31/2026
For centuries, steel has been a cornerstone material for structural construction; by contrast, adhesive joining is a relatively nascent technology, particularly in heavy structural applications. The present article aims to provide the reader a review of the applications of adhesive joining in steel-based applications. Steel being a popular material in many industries due to its excellent mechanical properties, but traditional joining methods might have certain limitations viz. ability to withstand vibrations or movement, distortion, difficult to repair, and the like. Adhesive joining provides an alternative approach that offers advantages like reduced weight, improved corrosion resistance, enhanced aesthetics, ability to join multi-materials, ability to resist vibrations to a certain limit, and the like. This article examines the use of steel within the automotive and construction industries, intentionally narrowing its scope from steel’s broader range of applications. This article
S., Shrray, Arora, Kanwer Singh
Test Procedures for Shear Strength of Automotive Brake Pads and Brake Lining AssembliesJ840_202603 (Current)3/31/2026
This SAE Recommended Practice covers equipment capabilities and the test procedure to quantify and qualify the shear strength between the friction material and backing plate or brake shoe for automotive applications. This SAE Recommended Practice is applicable to: bonded drum brake linings; integrally molded disc brake pads; disc brake pads and backing plate assemblies using mechanical retention systems (MRS); coupons from drum brake shoes or disc brake pad assemblies. The test and its results are also useful for short, semi-quantitative verification of the bonding and molding process. This Recommended Practice is applicable during product and process development, product verification and quality control. This Recommended Practice does not replicate or predict actual vehicle performance or part durability.
Brake Linings Standards Committee
From Stoplights to On-Ramps: A Comprehensive Set of Crash Rate Benchmarks for Freeway and Surface Street ADS Evaluation09-14-02-00033/31/2026
This paper presents crash rate benchmarks for evaluating US-based automated driving systems (ADSs) for multiple urban areas, distinguishing between freeway and surface street crash rates, and breaking them down by crash severity and type. The purpose of this study was to extend prior benchmarks focused only on surface streets to additionally capture freeway crash risk for future ADS safety performance assessments. Using publicly available police-reported crash and vehicle miles traveled (VMT) data from Arizona, California, Georgia, and Texas, the methodology details the isolation of in-transport passenger vehicles, road type classification, and crash typology. Key findings revealed that freeway crash rates exhibit large geographic dependence variations with any-injury-reported crash rates being approximately three times higher in Atlanta (2.3 IPMM; the highest) when compared to San Diego (0.7 IPMM; the lowest). The results show the critical need for location-specific benchmarks to
Scanlon, John M., McMurry, Timothy L., Chen, Yin-Hsiu, Kusano, Kristofer D., Victor, Trent
FITTINGS, INSTALLATION OF FLARELESS TUBE, STRAIGHT-THREADED CONNECTORSAS33566A (Current)3/30/2026
G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
Analyzing Effects of Cell to Chassis Technology on Sound Transmission Loss of Skateboard- Sharing Vehicles2026-01-50243/30/2026
Limited published research has critically examined the impact of Cell-to-Chassis (CTC) structures on the Noise, Vibration, and Harshness (NVH) performance of electric vehicles (EVs), with most studies focusing on conventional Cell-to-Pack (CTP) systems. A concern is that vehicles employing CTC architectures may exhibit compromised NVH performance due to the absence of a dedicated floor panel. To investigate the NVH performance implications of the CTC structure, this study adopts a comprehensive methodology encompassing: (1) theoretical Sound Transmission Loss (STL) analysis utilizing mass law and double-panel principles, (2) finite element (FE) modeling of STL, (3) in-vehicle Acoustic Transfer Function (ATF) testing, and (4) interior noise measurements conducted at a constant 60 km/h on a smooth asphalt road. Simulation results demonstrate that, compared to a conventional CTP floor system, the studied CTC structure achieves a 5–40 dB increase in STL across the 200–2000 Hz frequency
Xu, Xueying, Wang, Xiaoming, Ma, Caijun, Li, Guofu
BOLT, MACHINE - HEXAGON HEAD, PD SHANK, NICKEL ALLOY (UNS N07001), .1900-32 UNJF-3AAS3303B (Current)3/30/2026
E-25 General Standards for Aerospace and Propulsion Systems
The Study on Alternative Switching Noise Caused by Pulsating Magnetic Field Off Direct Current Ripple Induced by the Invertor Switching2026-01-50223/30/2026
As already well-understood/enormous engineering practices, the inverter AC-side NVH phenomena/mechanisms/measures for motor-equipped vehicle, are already pretty clear. In addition to inverter AC side–induced NVH issues, DC ripple induced by PE switching leads to NVH issues manifesting on the capacitor, inductor, and conductor in terms of reverse piezoelectricity, electrostriction, magnetostriction, Laplace force, and so forth. These DC-side NVH issues are already literally analyzed by a couple of literatures, and mechanisms/measures are explored/applied to electric drive development. And yet, the phenomenon that a pulsating magnetic field inside a battery pack induced by DC current ripple off PE switching brings noise at switching frequency inside the vehicle cabin is newly captured/analyzed by our research, and that has been barely searched during the literature survey. This newly discovered phenomenon is the pivotal point in this paper. Although the noise features like the
Zhao, Qian, Zhao, Yihan, Niu, Haolong, Li, Qiwei, Zhang, Wenchao, Xue, Hongbin, Cheng, Yanan, Li, Jing, Kang, Ming
STUD - STRAIGHT, RING LOCKED, CORROSION AND HEAT RESISTANT STEEL (UNS S66286), .3125-18 UNJC X .3125-24 UNJFAS3321F (Current)3/30/2026
E-25 General Standards for Aerospace and Propulsion Systems
BOLT, TEE HEAD – CHAMFERED, PD SHANK NICKEL ALLOY (UNS N07001),165 KSI MIN UTS .3750-24 UNJF-3AAS3235D (Current)3/30/2026
E-25 General Standards for Aerospace and Propulsion Systems
BOLT, MACHINE - HEXAGON HEAD, PD SHANK, NICKEL ALLOY (UNS N07001), .2500-28 UNJF-3AAS3307B (Current)3/30/2026
E-25 General Standards for Aerospace and Propulsion Systems
SAE TOMORROW TODAY - Powering Utilities Toward Net Zero135613/30/2026
What does it really take to build a clean energy future -- and who's stepping up to lead it? Listen in as we sit down with Steven Clarke, Program Director, Climate and Energy, Ceres, to explore how the organization is driving real-world climate solutions for Fortune 500 companies, investors, and policymakers though science-based, data-driven insights. From tackling water risk and data center cooling to scaling wind off the coast of New England, you'll learn how Ceres is transforming utilities, accelerating electrification, and reshaping entire industries for a cleaner, more resilient energy system. This conversation is proof that sustainability isn't just about responsibility, it's about opportunity. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and
Patterson, Lori
Leveraging Generative AI and Cloud Computing for Enhanced Autonomous Vehicle Systems a Software-Defined Architecture Approach2026-01-50233/30/2026
The rapid evolution of autonomous vehicle (AV) systems requires scalable, adaptable, and intelligent software architectures to cater for high demands in security, reliability, and real-time processing. This paper introduces a novel software-defined architecture combining generative artificial intelligence (AI) with cloud computing for extending the performance and capabilities of AVs. The proposed methodology uses generative AI models for dynamic perception, route planning, and anomaly detection and is implemented on cloud computing infrastructure to lend orders of magnitude larger computational resources for scaling on-the-fly learning among distributed AV fleets. Decoupling hardware-specific features and transitioning toward a software-defined paradigm, the processing platform allows for quick updates, continuous learning, and flexible deployment of world-leading AI models. Experimental results and simulated scenarios show better situational awareness, response time, and system
Namburi, Venkata Lakshmi
Effects of Vehicle Speed, Category, and Front-End Design on Full-Body Injury Risks of a Midsized Male Pedestrian09-14-01-00173/28/2026
This study investigated how vehicle front-end geometry, impact speed, and vehicle category influence injury risk to a midsize male pedestrian. Eighty-one generic vehicle (GV) models representing sedans, sport utility vehicles (SUVs), pickup trucks, and minivans sold in the United States were developed by morphing three base models using an automated pipeline. Front-end parameters that were varied included ground clearance (GC), bumper height (BH), hood leading-edge (HLE) height, hood length (HL), bumper lead angle (BLA), hood angle (HA), and windshield angle (WSA). Each vehicle impacted the Global Human Body Models Consortium 50th percentile male simplified pedestrian (GHBMC M50-PS) model at 30, 40, and 50 kph, totaling 243 simulations. Boundary conditions followed the European New Car Assessment Program (Euro NCAP) pedestrian test protocol. Thirty-five injury metrics were extracted across the head, neck, thorax, abdomen, pelvis, and lower extremities. Linear mixed-effects regression
Poveda, Luis, Miller, Logan E., Edwards, Colin C., Pollock, Madeline, Armstrong, William M., Hsu, Fang-Chi, Gayzik, Scott F., Weaver, Ashley A., Stitzel, Joel D., Devane, Karan S.
Characterization of Pedestrian Automatic Emergency Braking Acceleration in Modern Light Vehicles: Potential Implications for Occupant Safety09-14-01-00073/27/2026
The objective of this study was to characterize and compare pedestrian automatic emergency braking (PAEB) pulses in modern light vehicles to understand the loading environment that vehicle occupants are being exposed to during PAEB maneuvers. PAEB tests (n = 8008) conducted using 2018–2023 vehicle model years were analyzed. Pulse, vehicle, and impact characteristics (e.g., jerk, peak acceleration, pedestrian scenario, etc.) were derived from each PAEB test. Two k-means clustering analyses were used to group PAEB pulses with and without target collisions based on their similarity between characteristics. One-way ANOVA and Kruskal–Wallis tests were performed on the PAEB pulse characteristics to examine differences between clusters (p < 0.05). Two non-collision clusters (NC1 and NC2) were identified for PAEB pulses without collisions: NC1 had a statistically significant lower jerk (0.8 ± 0.4 g/s) and peak acceleration (1.0 ± 0.1 g) compared to NC2 (1.6 ± 0.8 g/s and 0.9 ± 0.1 g
Witmer, Maitland, Kidd, David, Graci, Valentina
Analysis and Determination the Time to Rollover of Tractor Semi-Trailer Vehicle Based on Multi-body System Analysis and Newton–Euler Equations02-19-03-00133/27/2026
This article aims to determine the time to rollover (TTR) of a tractor semi-trailer vehicle (TSTV). It uses a full dynamics model for assessment, specifically applying multi-body system analysis and Newton–Euler Equations with a nonlinear tire model. The model is applied to investigate velocities ranging from 40 km/h to 80 km/h and magnitude of steering angles ranging from 12.5° to 300°. The times at which the Load Transfer Ratio (LTR), Roll Safety Factor (RSF), and lateral acceleration reach their maximum values are evaluated. The survey results demonstrate the impact of velocity and steering wheel angle on the time it takes for the LTR, RSF, and lateral acceleration to reach their maximum values. The time interval between the RSF reaching 1 and the LTR reaching 1 range from 0.144 s to 0.655 s. Similarly, the time it takes for the tractor body’s lateral acceleration to peak and the LTR to reach 1 varies between 0.228 s and 1.555 s. Additionally, the time interval from when the semi
Hung, Ta Tuan, Khanh, Duong Ngoc
Control Strategy Optimization to Improve Energy Efficiency of Electric Wheel Loader Wheel Drive System02-19-02-00113/27/2026
Driven by the dual-carbon goals of “peak carbon emissions” and “carbon neutrality,” improving energy efficiency in electric construction machinery has become a key focus. This study proposes an energy-saving torque control strategy for the traction motor of electric wheel loaders, aiming to reduce drive system energy consumption. The innovation lies in coupling parameter optimization of the pedal–torque mapping and regenerative braking to enhance overall efficiency. An electric model was built using Cruise and validated against real-world V-cycle test data, showing good agreement with an average relative error of 4.08%. Based on the model, two optimized control strategies were developed and evaluated through simulations and field tests. The results showed energy savings of 7.08% and 16.18% in simulation, and 6.83% and 15.51% in tests, respectively, demonstrating the effectiveness and practical value of the proposed method.
Ming, Qiaohong, Wang, Yangyang, Wang, Feng
FITTING ASSEMBLY, RING LOCKED, ADAPTER, FLARELESS TO PORT, EXTRA FINE THREADS, 5080 PSIAS5550D (Current)3/27/2026
G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
Safety and Cybersecurity Recommendations for the Use of the Rust Language in Critical SystemsJA1020_202603 (Current)3/26/2026
This document provides guidance to using Rust in critical and safety-related software. The document summarizes how the usage of Rust supports in arguing safety according to ISO 26262 or RTCA DO-178C combined with RTCA DO-332. Cybersecurity best practices are referenced as these requirements largely overlap with those implemented for safety. As the Rust language is still evolving, this document targets the 2021 and 2024 editions of the language. Older or newer editions might require additional or changed rules and guidelines. Generally, the newest available edition of the language should be selected as newer editions remove ambiguities and outdated parts from the language.
Functional Safety Committee
Truck and Bus Aerodynamic Device and Concept TerminologyJ2971_202603 (Current)3/26/2026
This SAE J2971 Recommended Practice describes a standard naming convention of aerodynamic devices and technologies used to control aerodynamic forces on trucks and buses weighing more than 10000 pounds (including trailers).
Truck and Bus Aerodynamics and Fuel Economy Committee
Copper-Zinc Alloy, Laminated Sheet, 70Cu - 30Zn, Surface BondedAMS4508K (Current)3/25/2026
This specification covers a copper-zinc alloy (brass) in the form of laminated sheet with nominal thickness 0.006 to 0.125 inch (0.15 to 3.18 mm) (see 8.5).
AMS D Nonferrous Alloys Committee
CONNECTORS, RECEPTACLE, ELECTRIC, JAM NUT MOUNTING, FRONT RELEASE, CRIMP CONTACT, AN TYPEAS34041C (Current)3/25/2026
AE-8C1 Connectors Committee
Chassis Dynamometer Test Procedure - Heavy-Duty Road VehiclesJ2177_202603 (Current)3/25/2026
This SAE Recommended Practice has been adopted by SAE to specify: a. A standard procedure for chassis dynamometer testing of heavy-duty road vehicles for the purpose of determining power delivered through the drive tires. b. A method of correcting observed power to reference test conditions. c. A method of analyzing the test data to determine if the test results are within expected power ranges.
Engine Power Test Code Committee
Battery Industrial, Lead-Acid Type, for Use in Electric Powered Ground Support EquipmentARP1817B (Current)3/25/2026
This SAE Aerospace Recommended Practice (ARP) describes an industrial battery, lead-acid type, for use in electric powered ground support equipment.
AGE-3 Aircraft Ground Support Equipment Committee