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Vertical Flight Society Technical Papers - Coming Soon to Mobilus

Vertical Flight Society papers coming soon to SAE Mobilus. In partnership with the Vertical Flight Society (VFS), SAE Mobilus will be hosting more than 17,000 technical papers and proceedings from VFS. Click here to see a sample of the content covering decades of rotorcraft and vertical flight technologies.

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®

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

Browse All 177

Wing-in-Ground Effect Vehicles: From Modern Military and Commercial Development to Global Disaster Response

EPR202501711/24/2025

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 Engineering

EPR20250169/22/2025

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 Vehicles

EPR20250159/22/2025

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 Features

EPR20250138/13/2025

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 Robots

EPR20250128/13/2025

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 Vehicles

EPR20250147/18/2025

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 Intelligence

EPR20250115/21/2025

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 Mobility

EPR20250095/20/2025

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 Management

EPR20250085/20/2025

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 Earth

EPR20250054/24/2025

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

Browse All 16

Passenger Vehicle Systems

Electrified Vehicles

Advances and Current Practices in Mobility

Sustainable Transportation, Energy, Environment, & Policy

Connected and Automated Vehicles

Transportation Cybersecurity and Privacy

Vehicle Dynamics, Stability, and NVH

Transportation Safety

Alternative Powertrains

Materials and Manufacturing

Passenger Cars - Mechanical Systems

Recent Books

Browse All 722

Metallic Materials Properties Development and Standardization (MMPDS) Handbook - 2026 - Volume I

B-994_VOLUME17/1/2026

The Metallic Materials Properties Development and Standardization MMPDS-2026 supersedes MMPDS-25 and prior editions of the MMPDS Handbook as well as all editions of MIL-HDBK-5, Metallic Materials and Elements for Aerospace Vehicle Structures Handbook that were maintained by the U.S. Air Force. The last edition, MIL-HDBK-5J was cancelled by the U.S. Air Force in March 2006. This document contains design information on the mechanical and physical properties of metallic materials and joints commonly used in aircraft and aerospace vehicle structures. All information contained in this Handbook has been reviewed and approved using a standardized process. The development and ongoing maintenance process involves certifying agencies, including the FAA, DoD, and NASA, and major material suppliers and material users worldwide. The information and procedures in this Handbook are continuously reviewed and modified or removed as determined to be appropriate. With advances in materials and fastener

Metallic Materials Properties Development and Standardization (MMPDS) Handbook - 2026 - Volume II

B-994_VOLUME27/1/2026

Volume II publishes the framework for generating and analyzing the data so that material sponsors can generate the right data, knowing how it will be analyzed by the Battelle Memorial Institute. MMPDS-2026 Volume II Process Intensive Materials and Joining Technologies does not currently have any material properties, focusing on additive manufacturing of metallic materials. MMPDS-2026 Volume II focuses on non-conventional processes and will be published each year. Volume I: Conventional Materials and Joint Allowables.

1D and MultiD Modeling Techniques for IC Engine Simulation Second Edition

R-5805/29/2026

The internal combustion (IC) engine remains the most widely used thermal machine in the world and will continue to play a central role in global mobility for decades to come. Even as alternative powertrains expand, optimized IC engines—often integrated within hybrid and electrified architectures—are essential to achieving low fuel consumption, near-zero pollutant emissions, and reduced carbon dioxide output. Advances in combustion strategies, synthetic fuels, turbocharging, and aftertreatment systems are driving this evolution. This fully revised and expanded second edition reflects the rapid progress made in engine modeling and simulation over the past two decades. One-dimensional (1D), three-dimensional (3D), and coupled 1D–3D modeling techniques have become indispensable tools in modern engine design, enabling engineers to evaluate performance, efficiency, and emissions through advanced virtual engine environments. Bringing together contributions from leading international

Variable Compression Systems for Future Engines and Fuels

R-5534/30/2026

Variable Compression Engines: Enabling Net Zero explores variable compression ratio (VCR): one of the most promising—and historically elusive—advancements in internal combustion engine (ICE) technology. Long recognized for its thermodynamic benefits, VCR has challenged engineers for decades due to its mechanical complexity. Today, as the global mobility landscape demands ever higher efficiency, lower emissions, and greater fuel flexibility, VCR has emerged as a viable and transformative solution. This book delivers a comprehensive and authoritative examination of VCR technology, quantifying its efficiency and CO2-reduction potential while surveying the wide range of mechanisms conceived, developed, and tested over more than a century of engine innovation. By combining historical insight with modern analysis, the authors reveal the remarkable ingenuity of past and present engine designers—and demonstrate that VCR is not only feasible, but increasingly essential. Positioned squarely

Aerospace Standards Index - 2026

ASIN20262/25/2026

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 4

R-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 Index

AMSJAN-20261/24/2026

Fundamentals of Sustainable Aviation Fuels

R-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 Vehicles

R-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. 4

EPRCOMPV01202512/29/2025

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Research on Age-Friendly Design Strategies for Autonomous Buses Based on Service Design Concepts

2026-99-0536

7/10/2026

In the context of the accelerating development of an aging society, the inconvenient mobility of the elderly conflicts with the design of existing vehicles. The promotion and development of autonomous vehicles can provide solutions to this conflict to a certain extent. But existing autonomous vehicles lack a systematic age-friendly design. This study is based on a service design idea and employs the KJKANO hybrid model. The KJ method is used to construct a three-tier demand framework of “safety-function-emotion.” The KANO method is applied to identify the priority classification of each demand within the tiered framework. The study derives an aging-friendly design strategy for autonomous buses that prioritizes safety demands as the foundation, with functionality and emotional demands balanced accordingly. These strategies are then implemented in design practice. This study provides a user-centered systematic solution for the age-friendly design of autonomous buses, offering insights

Li, Wangyan, Ji, Yuanyuan

Simulation Analysis of Pure Electric Vehicle Equipped with Continuously Variable Transmission

2026-99-0522

7/10/2026

This study looks into the performance traits of a pure electric car that has a continuously variable transmission (CVT) system by doing careful simulations. The research is mostly about checking how well it performs dynamically and how much better its energy efficiency is compared to regular designs. With the help of AVL Cruise software, a detailed drivetrain model was made to test things like how fast it can accelerate, its top speed, how well it climbs hills, and how much energy it uses when driven in standard ways. The simulation results show some big improvements: the CVT car can go from 0 to 100 km/h in 12.92 seconds, which is 14% quicker than expected; it can reach a top speed of 179 km/h, 15% higher than planned; and it can climb really steep hills at a 41.33% gradient. The energy efficiency analysis also found that it uses less power, consuming just 15.88 kWh per 100km under NEDC conditions and 13.72 kWh per 100km in UDC cycles, which are 21% and 24% less than before. These

Chen, Haishan, Gong, Naifa, Pan, Yulong, Cai, Zhicheng, Gao, Yujie, Shen, Xiaobing, Fu, Xianlan, Chen, Keren

Design and Testing of a Quasi-Zero-Stiffness Vehicle-Mounted Isolation System with Additional Inerter

2026-99-0520

7/10/2026

Vehicle vibrations during precision instrument transport can cause damage and failure. Existing vibration isolators often lack reliability, mass production feasibility, and easy maintenance. In this paper, we design and analyze a quasi-zero-stiffness vehicle-mounted isolator with an inerter, decreasing dynamic stiffness while raising the effective mass. Theoretical, simulation, and experimental results show improved isolation performance, lower isolation frequency, and a broader isolation bandwidth.

Li, Kai, Lv, Sibo, Sun, Ning, Dai, Shijie

Temperature Influence Analysis and Compensation Method of Hemisphere Resonator Gyroscope

2026-99-0514

7/10/2026

Hemisphere resonant gyroscope (HRG) is a new type of vibration gyroscope with high precision, high reliability, and long lifespan. Improving the temperature stability of a hemispherical resonant gyroscope (HRG) has profound implications for navigation and guidance systems as well as airborne sensor technology. By optimizing temperature compensation algorithms or improving material thermal properties, the angular velocity measurement error caused by temperature drift can be significantly reduced, thereby improving the long-term positioning reliability of navigation systems in extreme temperature fluctuation scenarios. This article starts with the structure of the hemispherical resonant gyroscope, studies the temperature characteristics of the hemispherical resonator through formula theory, verifies and analyzes the temperature characteristics of the hemispherical resonant gyroscope through experiments, and designs a temperature compensation scheme. Through experimental data analysis

Wang, Jiachen, Chen, Pu, Yao, Zhiqiang, Zhang, Yi, Bai, Fan

2025 International Conference on Intelligent Transportation and Low Altitude Transportation (ITLAT)

2026-99-0500

7/10/2026

TOC

Tobolski, Sue

Traffic Flow Prediction System Based on Deep Learning

2026-99-0549

7/10/2026

Traffic flow prediction is of great significance for improving the operation efficiency of the transportation system, optimizing travel experience and reducing traffic congestion. Traditional traffic flow prediction methods are difficult to capture the spatio-temporal nonlinear characteristics of traffic flow due to its simple model and insufficient feature extraction ability. Therefore, an intelligent traffic flow prediction system based on deep learning is proposed, constructs a deep learning model based on graph convolution and fusion of attention mechanism LSTM. Based on this, a traffic flow prediction system is implemented. Experiments show that, on the PeMSD4 and PeMSD4 datasets, the error of the model in RMSE and Mae indicators is significantly reduced compared with the traditional methods, which provides an efficient solution for traffic flow prediction and congestion analysis, and has both theoretical innovation and engineering practical value.

Tang, Zhan, Lu, Xiaoyu, Yang, Nian, Xiang, Xiaohong, Hou, Xiang, Peng, Xiaoli

An Exploration of the Potential of Urban Linear Space under the Background of Fully Autonomous Vehicle System in Beijing

2026-99-0551

7/10/2026

The technology of autonomous vehicles has become the bellwether for the next transportation evolution. Based on the system of level 5 autonomous vehicles (fully autonomous vehicles), there will be space released from the existing urban context, including linear space, nodular space, and intersected space because of the enhancement of transportation efficiency and organization. The study took Beijing as an example to explore the linear space releasing potential under fully Autonomous Vehicles system to provide a reference for future urban planning. Considering saturation flow rate, speed, parallel throughput, vehicle occupancy, and safe headway, we quantitatively analyzed the potential release from various types of urban roads. The results shows that the expressways, arterial roads, secondary arterial roads, and branch roads could release up to 50%, 66% 50%, and 75% of the road space, respectively. The study verified that fully AV system can release great amount of public space, and

Ding, Yufei, Hou, Shuyu

Human-Machine Ergonomics Analysis of Civil Aircraft Electric Pilot Seats

2026-99-0570

7/10/2026

This paper uses a structured evaluation framework to study the ergonomics of electric pilot seats in modern civil aircraft. We have established a multi-level indicator system to examine the adjustability, pressure distribution, dynamic response and, fatigue relief effect of the seat. All experimental data were obtained from a full-scale cockpit simulator environment, where a ground-based mock-up and motion-free simulated cockpit were used to replicate real operational posture, control-reach conditions, and long-duration mission loads. This framework combines experimental measurement and fuzzy evaluation techniques to quantify the quality of human-computer interaction. Test results show that compared with ordinary seats, the prototype seat has a wider adjustment range, a more uniform pressure distribution, and a smoother dynamic response. It is particularly worth mentioning that it can delay the emergence of fatigue during long-term operation, which proves the advantages of the electric

Tian, Yanan, Pi, Zhengyang

Voltage Regulation and Limits

J3226_202607 (Current)

7/10/2026

This document defines the test procedures and performance limits of steady state and transient voltage characteristics for 12 V, 24 V, or 48 V electrical power generating systems used in commercial ground vehicles.

Truck and Bus Electrical Systems Committee

Impact of Driving Style on Electric Vehicle Energy Consumption

2026-99-0507

7/10/2026

The way we drive has a big effect on how much energy electric cars use, so making better driving habits can help make electric cars use less energy. By utilizing a set of real EV driving data, this paper classifies and analyzes EVs from the perspective of energy consumption, and establishes an intelligent scoring system for EV driving behavior based on a decision tree model. Experimental results show that this method is able to successfully distinguish different driving behaviours and the critical driving behavior factors, such as vehicle speed, accelerator pedal change rate, etc., and braking behavior are identified. Use intelligent scoring to give driver suggestions; this way, they can improve on their driving techniques and lower their energy consumption.

Liang, Yongkai, Zhang, Hao, Liu, Yu, Yu, Hanzhengnan

Study on Mechanical Performances and Fatigue Life of the Compensation Ropes in High-Speed Railway Contact Network

2026-99-0515

7/10/2026

The compensation rope is a special steel wire rope used as a driving component in the ratchet device. The compensation rope will endure severe random cycling loading during service time, which will lead to fatigue failures and catastrophic disasters. Experimental studies are hard to mimic the practical working conditions and time consuming, therefore, this study establishes a finite element model of the compensation rope and simulates the stress distribution under axial tensile and bending loads. Fatigue life is analysed based on both stress and strain fatigue theories under alternating tensile and bending loads. The results indicate that under axial tensile loads, the stress in the outermost wires of the core strands of the compensation rope is the largest, with the minimum fatigue life. As the stress ratio of the alternating tensile load increases, the fatigue life also improves due to smaller stress amplitudes. Under the conditions of bending loads, the outermost wires of the

Du, Fei, Cong, Jiajia, Bian, Haoxiang, Zhu, Junchen, Zhao, Aiguo

Disaster Evolution and Risk Evaluation of Urban Transport Infrastructure under Extreme Rainfall–Flood Scenarios: A Case Study

2026-99-0554

7/10/2026

To investigate the disaster evolution characteristics and associated risks of heavy rainfall and flooding on urban transportation infrastructure, this study takes the extreme rainstorm event in Zhengzhou as a typical case. A multidimensional dynamic risk assessment model is employed to analyze the disaster evolution process and conduct risk evaluation. First, the three-stage evolution process and its characteristics are systematically examined. Then, based on the theory of natural disaster risk elements, a dynamic risk assessment model is constructed. The improved Order of Priority Approach (OPA) is used to determine the weights of multidimensional risk factors, and interval type-1 fuzzy logic is introduced to address the uncertainty of fuzzy indicators. Finally, the overall risk level of the heavy rainfall–flooding disaster chain is calculated and evaluated. The results indicate a high-risk level, which is consistent with the findings of the field investigation report, thereby

Zhang, Yongcheng, Wang, Jianwei, Wu, Ziyi, Wang, Yan, Luo, Qing, Kang, Pingping

Influence of Eccentric Chamfer Structure at Seat Ring Bottom Hole on Swirl Ratio and Flow Coefficient in Dual-Tangential Intake Ports

2026-99-0524

7/10/2026

The airflow characteristics of engine intake ports significantly influence combustion efficiency and emission performance. This study investigates the effects of an eccentric chamfer structure at the seat ring bottom hole on the swirl ratio and flow coefficient in a dual-tangential intake port for a four-valve diesel engine. Computational fluid dynamics (CFD) simulations and steady flow experiments were conducted under valve lifts ranging from 1 mm to 9 mm. Results indicate that the eccentric chamfer structure enhances the swirl ratio by 39 times (from 0.12 to 4.73) at low valve lifts (<6 mm) without compromising the flow coefficient. At higher lifts (>6 mm), both chamfer designs exhibit negligible differences in performance. Experimental validation confirmed the CFD results, with errors below 3% for swirl ratio and 5% for flow coefficient. This work provides a practical approach to optimize low-speed engine performance through geometric modifications.

He, Shuchao, Li, Ying, Shi, Yanfei

Dynamic Routing Optimization of Electric Garbage Collection and Transportation Vehicles Based on Smart Dumpster

2026-99-0550

7/10/2026

The comprehensive deployment of smart garbage bins realizes the real-time monitoring of garbage generation and recycling demand, and the use of intelligent network connected collection and transportation vehicles can sense dynamic data such as vehicle location and load in real time. In this context, how to efficiently integrate these dynamic information to build a responsive scheduling system has become a key requirement of smart city management. Aiming at this requirement, this paper proposes a dynamic routing optimization model of electric garbage collection and transportation vehicles considering charging constraints, and designs a hybrid PSODE combining improved particle swarm optimization(PSO) and differential evolution(DE) to solve the model. By introducing a nonlinear decreasing strategy of inertia factor and a dynamic learning factor adjustment mechanism, an adaptive optimization framework of algorithm parameters is established to enhance the adaptability of the algorithm

Shen, Xiaolong, Ma, Huimin

Effect of Micro-Morphology on Thermal Radiation Properties of TC4 Alloy

2026-99-0512

7/10/2026

With the development of manned spaceflight and deep space exploration, TC4 alloy has been used for the structure design of aircraft due to its excellent characteristics. Thermal radiation properties (solar absorptance and hemispheric emittance) of TC4 alloy are becoming important design indices. We investigated TC4 alloys with different surface morphologies and the effect of micro-morphology on thermal radiation properties. The results show that the solar absorptance of the alloys is sensitive to surface roughness and microstructure. As the surface roughness or crack increases, solar absorptance increases. Hemispheric emittance of the alloys increases as surface roughness is added, but it is insensitive to the micro-nanostructure of the alloys.

Liu, Yang, Zhu, Xiaoxi, Ren, Chaolong, Li, Dasong, Wan, Lei, Huang, Feiyu

Traffic Crash Prediction and Causal Disentanglement by Machine Learning

2026-99-0552

7/10/2026

Aiming at the problem of insufficient modeling of spatio-temporal heterogeneity in road traffic accident prediction, a dual task machine learning framework integrating geographical environment, location attributes and time periodicity is proposed. The dataset used in this study was derived from traffic accident records of Nanchang during 2019–2023. Firstly, geographical identifiers are generated by rounding and aggregating latitude and longitude coordinates. At the same time, the location type is processed by a one-hot encoding, so as to carry out spatial clustering analysis of accident hotspots. Compared with the North-South pattern, the contribution of geographical features shows a strong East-West trend. The kernel density heatmap identified Zone A and zone B as dual core high-risk areas. Secondly, the sinusoidal/cosine function is used to encode the time feature circularly, which effectively captures the daily change of the accident. The quantitative analysis of random forest

Luo, Jiang, Zhang, Yuxin, Li, Xin, Wu, Ronghai

Research on Urban Bus Timetable Optimization Based on Deep Reinforcement Learning

2026-99-0538

7/10/2026

Public transportation serves as a crucial component of urban mobility, contributing to the alleviation of urban congestion, reduction of travel expenses, and mitigation of air pollution. Nonetheless, the dynamic passenger demand and the complex traffic conditions render traditional bus timetables inadequate, leading to ineffective allocation of public transportation resources. Consequently, it is essential to create bus timetables that are responsive to actual traffic scenarios and fluctuating passenger demand. This study regards the bus timetable planning problem as a Markov decision-making process within a discrete time framework, proposing a deep reinforcement learning-based optimization model for bus timetables. In particular, the model is designed to account for both bus companies and passengers, incorporating a state space and reward calculation method that emphasizes passenger comfort. Then Deep Q-Network (DQN) methodology is employed to issue instructions on whether a bus

Xu, Jie, Xia, Dong, Yang, Jianxi, Wang, Bing

Research Review on Data Fusion-Based Ship Information Perception Technology

2026-99-0571

7/10/2026

With the development of domestic vessel traffic service (VTS) systems, China has established a comprehensive maritime traffic management infrastructure. Marine sensing equipment, including radar, the automatic identification system (AIS), and electro-optical (EO) systems, provides diverse sources of ship information. In recent years, data fusion technology has attracted increasing attention for its potential to improve the accuracy and completeness of ship perception. This paper introduces key ship information sensing technologies and examines the distinct characteristics of each approach. It then reviews recent advances in three main areas: vision-based ship feature recognition, multi-source data association analysis, and ship motion prediction. Finally, the paper outlines prospective research directions, including the integration of additional data sources, real-time data processing, enhanced data security, and intelligent maritime decision-making.

Zhao, Kui, Song, Zheming, Huang, Yuantao

The Chain of Visual Factors, Visual Characteristics, and Driving Behavior at Highway Tunnel Entrances

2026-99-0556

7/10/2026

To explore the impact of guiding and warning visual combination factors at the entrance sections of highway tunnels on drivers’ visual characteristics and driving behavior, this study recruited 16 drivers to conduct on-road vehicle experiments at the entrance sections of the Yunling Tunnel’s left bore (with visual combination factors) and right bore (without visual combination factors). Seven visual characteristics and driving behavior indicators, including pupil diameter and vehicle speed, were collected and statistically analyzed. Representative indicators such as pupil diameter, standard deviation of fixation point position, and vehicle speed were selected to establish a trend surface model of visual characteristics and driving behavior. The results indicate that when driving at the entrance section of the left bore, drivers’ pupil diameter and fixation duration were significantly lower than those at the entrance section of the right bore. With the increase in the sweeping view

Ma, Yanpeng, Huang, He, Huang, Yong, Yuan, Chen

Design and Analysis of Orthogonal Excitation Eddy Current Brake for High-Speed Trains

2026-99-0513

7/10/2026

As high-speed train technology advances, the demands on braking system performance have intensified. Known for their efficiency, reliability, and eco-friendliness, Linear Eddy Current Brakes (LECB) have become a focal point in the research and development of high-speed train braking systems. This paper presents an innovative Orthogonal Excitation Eddy Current Brake (OEECB), which enhances the braking force without modifying the overall dimensions of the conventional LECB. By adding a set of longitudinal excitation coils parallel to the rail surface, the OEECB creates an orthogonal excitation structure that augments the braking force. Initially, this paper outlines the design concept of the OEECB and then analyzes its working principle based on electromagnetic field theory. Subsequently, a finite element solver is employed to numerically model the electromagnetic characteristics of the OEECB. Finally, by comparing the performance differences between the conventional LECB and OEECB, the

Huang, Liuwen, Zuo, Jianyong, Zhang, Yu

Researchon Key Technology Optimizationof Automotive Magnetic Continuously Variable Transmission

2026-99-0509

7/10/2026

Traditional mechanical continuously variable transmission (CVT) has a complicated structure. During the transmission process, the master and slave wheels rub against each other to produce chattering and heat loss, and the master and slave wheels are seriously worn. In order to improve the transmission efficiency and reliability of continuously variable transmission, Automotive magnetic CVTs (Manetti Continus, Livaria, Breitlans, Mack) were used as research objects. By establishing the efficiency model of key parts, the relationship between the efficiency of each component and different parameters is transformed and calculated, and then it is optimized using Matlab. The finite element analysis of a permanent magnet eddy current speed regulating device is carried out by using finite element Ansys Maxwell, and the relationship curve between the average meshing area and each parameter is analyzed. The results show that the volume of the optimized gear train is reduced by about 51.7

Zhou, Dan, Zhang, Bolin

Nonconvex Quadratic Programming Problem for Ship Magnetic Dipole Array Model

2026-99-0587

7/10/2026

The magnetic field modeling methodology for ships based on magnetic dipole arrays demonstrates heightened sensitivity to input data. When addressing overdetermined systems characterized by numerous variables and constrained measurement points, the coefficient matrix frequently develops pathological ill-conditioning, leading to solution divergence and compromised result accuracy. This research reformulates the ship magnetic field inversion challenge as a non-convex quadratic programming problem, employing the Successive Convex Approximation (SCA) algorithm as the computational solver. Rigorous comparative validation was performed against conventional stepwise regression algorithms and experimental datasets acquired from scaled ship model measurements. Results substantiate that while the modeling precision of the SCA algorithm remains comparable to that achieved by stepwise regression methods, SCA exhibits demonstrably superior solution stability. This enhanced robustness positions SCA

Chen, Hao, Pan, Xun

Optimizing Autonomous Obstacle Avoidance with PON Architecture and SDN-Based Dynamic Scheduling

2026-99-0592

7/10/2026

This study addresses the challenges of communication delays and system stability in autonomous obstacle avoidance (AOA) systems under next-generation vehicular electronic/electrical architectures. A centralized PON-based architecture is proposed, leveraging XGSPON technology to enhance bandwidth capacity and reduce electromagnetic interference, while rigorously analyzing worst-case in-vehicle communication (IVOC) delays. To mitigate latency impacts, a Software-Defined Networking (SDN)-driven dynamic scheduling strategy prioritizes safety-critical data streams (e.g., environmental perception, motion control) through adaptive resource allocation. Further integrated with a robust H-infinity LQR controller, the co-design framework ensures precise trajectory tracking and suppresses steering oscillations under communication uncertainties. Simulation tests validate the framework's efficacy, demonstrating significant reductions in loop delays and improved dynamic stability in complex scenarios

Wang, Wenwei, Han, Muchen, Cao, Wanke

Distributed Control Method and System of Formation Train Based on Multi-Objective Operation Curve Optimization

2026-99-0555

7/10/2026

In order to improve the transportation efficiency of high-speed trains, reduce the operational energy consumption and ensure the on-time arrival of trains, the operation curve optimization is regarded as a key way to achieve the above objectives. In this paper, a distributed control method and system for grouped trains based on multi-objective running curve optimization is introduced. Firstly, the train dynamics equations are established by considering the combined forces during train operation and the train driving maneuvering strategy, combining with the line conditions, and dividing the train operating conditions; secondly, combining with the virtual grouping technology, the train units are kept in a high safety and smooth tracking operation with small intervals between the train units; and then the constraints, such as setting up safety protection distance and Then, the constraints of safety protection distance and space-time safety protection are set, and with energy-saving and

Jiang, Qiqi, Chen, Guangwu, Shi, Jianqiang, Wang, Dong, Si, Yongbo, Li, Peng, Zhang, Wentao, Yang, Yang

Multi-Objective Optimization Research and Design of Seat Structure in Vehicle Collision

2026-99-0518

7/10/2026

The vehicles often accompanied by a huge impact in the collision process, high-quality and high-strength car-seats can better protect the safety of passengers. However, in the call for vehicle energy saving and emission reduction, the lightweight design of car-seats is imminent. Therefore, it is necessary to achieve lightweight seat weight while ensuring vehicle safety. Based on the dynamic condition of vehicle collision, this paper takes the rear seat of a certain model as the research object, takes multiple responses of the seat skeleton system as the target, establishes a multi-objective optimization model of the seat skeleton, determines the optimization result with the greatest comprehensive satisfaction, verifies the optimization result of the seat skeleton. The correctness and feasibility of the design method are proved.

Shao, Youlin, Ni, Weiyu, Chen, Daojiong, Cheng, Zhiqing

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