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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 advanced air mobility and drone industry further enable the development of modern, safe, and practical WIG platforms. Click here to access the full SAE EDGETM Research Report portfolio.

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 mitigation of algorithmic biases. Click here to access the full SAE EDGETM Research Report portfolio.

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 actionable solutions to help stakeholders better navigate the transition toward a circular future for mobility. It further highlights the overlooked complexities in the Global South, emphasizing the importance of ethical market expansion and localized mobility strategies. Click here to access the full SAE EDGETM Research Report portfolio.

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 suggestions for future research will also be discussed. Click here to access the full SAE EDGETM Research Report portfolio.

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 track, as well as the economics of moving capital intensive automation systems toward a service-provision business model. Click here to access the full SAE EDGETM Research Report portfolio.

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 Control for Autonomous Vehicles presents a hybrid framework that combines data-driven insights with the robustness of physical models. It identifies key challenges in fusing these disparate methods and outlines potential solutions in developing robust fusion strategies, establishing generalized mixed dynamics models, and designing multi-objective robust control systems. In addition, the report explores future research directions to enhance learning efficiency, improve adaptability to rare but critical scenarios, and ultimately pave the way for secure, efficient, and human-like autonomous driving systems. Click here to access the full SAE EDGETM Research Report portfolio.

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 redefined what it means to be a "product." Click here to access the full SAE EDGETM Research Report portfolio.

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 intelligence (AI) is instrumental in processing such data, and in that context, “edge AI” is a more recent type of implementation. Edge AI involves AI algorithms in edge computing devices, which requires hardware operating close to where data is generated. This report explores the potential of edge AI in CCAM. Different perspectives on edge AI for CCAM are explored and definitions drafted. Primary applications are explored, and an outlook on further advancements in applications is presented. The report includes a discussion on the benefits, risks, and challenges related to the use of edge AI in this domain. Major issues such as privacy and cybersecurity are considered, as are misconceptions. Furthermore, potential learning benefits, using experiences gained in other sectors, are introduced. NOTE: SAE Edge Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. These reports are not intended to resolve the challenges they identify or close any topic to further scrutiny.

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 educational programs in leveraging AI for transportation applications are emphasized in this report. Click here to access the full SAE EDGETM Research Report portfolio.

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

Transportation Cybersecurity and Privacy

Connected and Automated Vehicles

Vehicle Dynamics, Stability, and NVH

Transportation Safety

Alternative Powertrains

Commercial Vehicles

Passenger Cars - Mechanical Systems

Passenger Cars - Electronic and Electrical Systems

Fuels and Lubricants

Materials and Manufacturing

Engines

Recent Books

Browse All 633

Ceramic Matrix Composites

R-4608/27/2026

The fifth volume of this compendium publishes technical guidelines and properties of ceramic matrix composite material systems. The content includes information on material selection, processing, characterization, testing, data reduction, design, analysis, quality control, application, case histories, and lessons learned of typical ceramic matrix composite materials. Initial Release of Volume 5 superseded Mil-HDBK-17-5 dated June 17, 2002. The Composite Materials Handbook, referred to as CMH-17, is an engineering reference tool that provides comprehensive, practical engineering guidelines that have proven reliable for the design, fabrication, characterization, test, and maintenance of polymer matrix, metal matrix, ceramic matrix, structural sandwich, and non-metallic AM materials. CMH-17 provides information and guidelines necessary to design and fabricate end items from composite materials. The compendium includes reliable data, linked to control of processes and raw materials, to provide material property basis values and design information that promotes the safe use of ceramic matrix composites in aerospace applications. CMH-17 provides information and guidelines necessary to design, fabricate, and maintain components from composite and non-metallic additively manufactured (AM) materials. In support of this purpose, the handbook constitutes an overview of the field of advanced materials technology and engineering. It is used by engineers worldwide in designing and fabricating products made from composite materials.

July 2026 AMS Index

AMSJULY-20267/22/2026

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 systems, and with the review process of existing information, periodic updates of the MMPDS should be expected. As such, it is recommended that the latest version of the MMPDS be used. Volume II: Process Intensive Materials and Joining Technologies.

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 researchers and industry experts, this book presents the most significant and recent developments in IC engine simulation. Topics include 0D, 1D, quasi-3D, and full 3D modeling approaches; turbocharging and aftertreatment systems; co-simulation and real-time applications; hydrogen and two-stroke engines; and advanced thermal modeling techniques. Designed for engineers, researchers, and graduate students, this second edition serves as a comprehensive reference for understanding, comparing, and applying state-of-the-art IC engine modeling methodologies in an evolving mobility landscape. Chapter topics include: • state of the art of 1D thermo-fluid dynamic simulation models • virtual engine development: 1D- and 3D-CFD up to full engine simulation • advanced 0D and quasiD thermodynamic combustion models for SI and CI engines • compressor and turbine (turbocharger, supercharger, or turbocompounding device) as boundary conditions for 1D simulations • 3D-CFD combustion models for SI and CI engines • model order reduction for real-time simulation and control applications • modeling of EGR systems •1D engine model in XiL application-a simulation environment for the entire powertrain development process • coupling of 1D and 3D fluid dynamic models for hybrid simulations • extending the 1D approach to the simulation of 3D components: the quasi-3D approach • 1D simulation models for aftertreatment components• 3D simulation models for after-treatment systems • modeling of IC engine silencers and tailpipe noise: 1D and 3D approaches • hydrogen-fueled internal combustion engines • optimization of the gas exchange process in advanced 2-stroke engines • IC engine 0D/1D thermal modeling

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 within the context of global decarbonization, the book argues for a realistic, inclusive pathway to net-zero emissions—one in which ICEs continue to play a critical role. VCR technology enables higher efficiency across almost all operating conditions, supports advanced combustion strategies, and allows engines to operate effectively on a broad spectrum of low- and zero-carbon fuels, from biofuels to synthetic e-fuels. With VCR now in high-volume production and poised for broader adoption across automotive, heavy-duty, and marine applications, this timely volume is an essential resource for OEMs, suppliers, policymakers, researchers, and students seeking practical, scalable solutions for a sustainable energy future. Chapter topics include: • compression ratios and fuels • compression ratio limits • cylinder head VCR • cylinder block VCR • connecting rod variable compression • piston VCR • cranktrain and linkages VCR • modulated crankshaft eccentricity VCR • axial or barrel engine VCRs • high power and downsized engines • impact of VCR systems on engines • VCR applications for the future • variable compression for future engines and fuels • VCR cost–benefit analysis

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 include: • Holistic reliability across design, manufacturing, supply chain, and marketing. • Advanced experimental designs, including split-plot and fractional factorial methods. • Fault tree analysis (FTA) and FMEA for failure prediction and prevention. • Supply chain optimization through multivariate process control. • Production and field reliability using design for testability and diagnostics. • Electric vehicle system and battery reliability analysis. • Marketing reliability driven by voice of customer and data-based value analysis. This book is an essential resource for engineers, operations leaders, and technical managers who want to build resilient systems, unlock innovation, and achieve long-term competitive advantage through disciplined, data-driven reliability.

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 performance and emissions reduction potential; safety, certification, and market integration; and future projections supported by international initiatives and regulatory frameworks. By combining technical depth with practical relevance, Fundamentals of Sustainable Aviation Fuels serves as both a foundational reference and a forward-looking guide for researchers, policymakers, industry professionals, and students. It underscores that achieving sustainability in aviation depends not only on innovation but also on global collaboration, paving the way toward cleaner skies and a resilient, low-carbon future for air travel.

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 global standards, research, and innovations, this dictionary bridges the gap between theory and application. It fosters interdisciplinary collaboration, supports safer system design, and provides clarity for those engaged in regulatory development or technology deployment. As the pace of mobility innovation accelerates, precise and accessible communication becomes indispensable. SAE International remains committed to advancing global transportation knowledge—empowering professionals to navigate, contribute to, and shape the future of intelligent, connected, and sustainable mobility with confidence and clarity.

Recently Published

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Overpressurization Release Devices

ARP1322D (Current)

11/13/2026

This SAE Aerospace Recommended Practice (ARP) specifies the minimum design and qualification test recommendations for aircraft wheel overpressurization release devices used with tubeless aircraft tires to protect from a possible explosive failure of the contained inflation chamber due to overinflation.

A-5A Wheels, Brakes and Skid Controls Committee

Thermal Sensitive Inflation Pressure Release Devices for Tubeless Aircraft Wheels

AS707D (Current)

11/13/2026

The focus of this SAE Aerospace Standard (AS) is the integration of thermally actuated pressure release devices, hereafter referred to as fuse plugs, with the wheel and brake assembly. It does not address the manufacturing, quality, or acceptance test requirements pertaining to the production of these fuse plugs. It establishes minimum design, installation, qualification, and operational requirements for fuse plugs which are used only in tubeless tire-type aircraft braked wheels. Fuse plugs are designed to completely release the contained inflation pressure from a tubeless tire and wheel assembly when brake generated heat causes the tire or wheel to exceed a safe temperature level. The objective is to prevent tire or wheel rupture due to brake generated heat that could cause an unsafe condition for personnel or the aircraft. Refer to FAA Advisory Circular (AC) No. 23-17C; 14 CFR Part 25.735 (j); FAA AC No. 25.735-1; FAA AC No. 25-7D; EASA Certification Specifications for Large Aeroplanes (CS-25) 25.735 (j); and AMC 25.735.

A-5A Wheels, Brakes and Skid Controls Committee

Steel, Corrosion-Resistant, Sheet, Strip, and Plate, 18Cr - 8Ni (SAE 301), Solution Heat Treated

AMS5901E (Current)

11/13/2026

This specification covers a corrosion-resistant steel in the form of sheet, strip, and plate.

AMS F Corrosion and Heat Resistant Alloys Committee

Collision Risk Prediction for Autonomous Vehicles Based on GTWR-HOLT

2026-99-2010

11/13/2026

Autonomous vehicles face constraints from multiple factors, including insufficient technological maturity, complex urban road network structures, and behavioral uncertainties of traffic participants. Consequently, their driving safety has not yet been fully verified and guaranteed. To address the gaps in existing research, such as the lack of spatiotemporal dimension-specific prediction and insufficient utilization of higher-level autonomous vehicle accident data, a Geographically and Temporally Weighted Regression (GTWR)-HOLT accident risk prediction model was constructed. This model integrates accident severity and frequency while accounting for spatial heterogeneity and temporal non-stationarity. Based on collision accident data from autonomous vehicles in California, USA, for the period 2021-2023, and integrating multi-source data including road networks, Points of Interest (POI), and population, this study conducts empirical research by dividing the study area into spatiotemporal grids with a spatial step of 2 km × 2 km and a temporal step of one quarter. GTWR analysis of the first ten quarters of data shows a Mean Absolute Error (MAE) of 0.05, with predicted values closely matching the trend of the actual values, effectively capturing the variation patterns of risk. Commercial POI density, educational POI density, and population density consistently exhibit positive effects on accident risk. The risk prediction results for the eleventh quarter using the HOLT exponential smoothing model yield an MAE of 0.08. The results indicate that medium-high risk areas are likely to maintain their current risk levels in the near term. Predictions for low-to-medium risk areas and some high-risk areas perform well, and the predicted regression coefficients largely follow the trends of the original coefficients. The research provides data-driven support in formulating regulatory strategies for traffic management authorities and algorithm improvement measures in complex scenarios for vehicle manufacturers.

Wu, Shaoping, Hou, Yi, Dong, Chunjiao, Lu, Zhenzhen, Lai, Zhijian, Wen, Hang

Analysis of Competition and Cooperation Relationship between Ride-Hailing and Subway

2026-99-2014

11/13/2026

Due to the rapid growth in ride-hailing services and the steady expansion of urban rail transit networks, understanding the complex interaction between the two is important. Most existing studies only focus on the overall competition and cooperation effects. Few scholars discuss local spatial differences and how the built environment works in detail. To investigate the spatial heterogeneity of built environment factors between the ride-hailing and the subway systems by situation and location, our study categorizes 3.71 million ride-hailing trips into three types: Proximal-to-Station Trip (PST), Medial-to-Station Trip (MST), and Distal-to-Station Trip (DST). We employed the values of built environment factors per grid as independent variables, and the grid-based volume of each ride-hailing trip category (PST, MST, DST) as the dependent variable. Additionally, we conducted analysis mainly with the multi-scale geographically weighted regression model (MGWR). We found that ride-hailing trips and subway trips have competition, cooperation, or complementarity relationships, which depend on trip purposes and public transit accessibility. Besides, we think that this relationship relies on the built environment, and it also shows clear spatial heterogeneity. The impact of different built environment factors has significant variation and spatial heterogeneity: Catering, Shop, and Bus Stop continuously trigger the demand for ride-hailing services, while Residence generally reduces the use. In PST, Enterprise, Medical, and Residence inhibit ride-hailing due to the high subway accessibility. In DST, these functions conversely boost ride-hailing usage due to limited bus coverage. These findings provide crucial insights for smart transportation management, multi-modal, and location-specific strategies to boost sustainable urban transportation development.

Zhao, Shiya, Xiao, Lingling

Resistance Resilience Assessment of High-Speed Rail Transport Networks Based on Hypergraph Theory

2026-99-2020

11/13/2026

The high-speed rail network plays a crucial role in the development of the national economy and national defense, and assessing its resilience is of great significance for ensuring transportation safety and supporting emergency decision-making. To address the limitations of traditional complex network models in capturing multifaceted, higher-order interactions, this paper constructs a high-speed rail transport hypernetwork model based on hypergraph theory and evaluates the resilience of the high-speed rail transport hypernetwork from two dimensions: hypernetwork structure and hypernetwork function. By conducting experiments on the sequential failure of design nodes, this study compares the performance evolution and resilience boundaries of high-speed rail transport supernetworks under scenarios involving random and targeted attacks, thereby providing a theoretical basis for optimizing the resilience of high-speed rail transport networks. This study focuses on the high-speed rail network in the middle reaches of the Yangtze River and conducts an empirical analysis based on data from 1,085 high-speed rail services operating on October 22, 2025. The results indicate that structural resilience is superior to functional resilience, and that networks exhibit greater resilience against random attacks than against targeted attacks. A small number of core nodes handle the network’s primary functions; if they fail, network performance will decline significantly. Attacks based on betweenness centrality are the most destructive, while those based on sub-hypergraph centrality are relatively the least destructive. Hypergraph-based hypernetworks can effectively account for the operational relationships among high-speed trains, capture the association patterns between nodes, and provide a more accurate theoretical approach for modeling high-speed rail transport networks. This paper employs hypergraph theory to construct a hypernetwork of high-speed rail transportation, taking full account of the operational relationships among high-speed train services to enhance the accuracy of research on network resilience. This paper provides a theoretical framework for assessing and enhancing the resilience of high-speed rail networks and is of great significance for promoting the sustainable development of the railway sector.

Du, Hongwei, Tu, Min

Measurement and Structural Reliability Research of Wind-Driven Rain Pressure Loads on Low-Rise Buildings under Extreme Weather Conditions

2026-99-2035

11/13/2026

The objective of this study is to examine the effects of wind-driven rain pressure loads on the structural reliability of low-rise buildings under extreme weather conditions. Pressure sensors, rain sensors, and wind measuring devices were installed on the surfaces of representative low-rise building samples. Load characteristics, including load magnitudes, distributions, and variation tendencies, were measured under different wind speeds, directions, and rain intensities over long periods, with correlation analysis carried out for all relevant parameters between loads and meteorological factors. A mechanical modeling framework was developed that takes into account uncertainty associated with wind-driven rain pressure loads, materials, and structural geometries. Failure probabilities and reliability indices were calculated for different critical structural components using reliability theory, with a focus on potential modes of failure and reliability deterioration due to fatigue. Based on the above investigation, optimal design guidelines were proposed, and their feasibility was confirmed by several engineering applications.

Zhang, Yutong

ST-ParFusion: Spatio-Temporal Parallel Fusion Network for Traffic Flow Prediction Based on Multi-Relation Driving

2026-99-2013

11/13/2026

Accurate and real-time traffic state prediction is fundamental to optimizing urban traffic control and improving the service quality of online mapping platforms. While data-driven deep learning methods have shown promise in handling large-scale data, most existing approaches suffer from limitations due to their reliance on simplistic modeling components that cannot fully capture complex and multi-scale spatiotemporal dependencies. Unlike prior studies that predominantly utilize static graph structures or sequential processing, this research addresses the challenge of modeling dynamic correlations by proposing a Spatiotemporal Parallel Fusion Network. The theoretical framework of this study integrates graph spectral theory with advanced attention mechanisms to model both the physical and semantic topology of traffic networks. The proposed methodology features a multi-source spatial modeling framework that fuses a static connectivity graph, an inverse distance weighted graph, and a flow similarity graph via multi-relational graph convolution. This approach allows for the simultaneous capture of physical connectivity and dynamic traffic patterns. Furthermore, utilizing a parallel architecture, the temporal modeling component integrates multi-head self-attention with two-dimensional causal dilated convolutions. A cross-attention fusion module is further introduced to dynamically regulate spatiotemporal interactions. Comprehensive tests conducted on four practical traffic datasets indicate that the introduced model significantly outperforms thirteen cutting-edge benchmark methods. The study confirms that the proposed multi-graph strategies and parallel architectures effectively reduce mean absolute error and root mean square error, validating the efficacy of the proposed solution for the advancement of intelligent transportation systems.

Chen, Lulu

A Roadside Monocular Vision Method for Target Ranging and Speed Estimation Using 3D Object Detection

2026-99-2016

11/13/2026

With the development of intelligent transportation systems, roadside video perception is expanding from traditional detection and tracking to higher-level measurement outputs, such as inter-target distance and target speed. These measurements are important for traffic flow estimation, accident warning, and timely responsibility assessment after incidents. Monocular cameras offer low cost, easy deployment, and wide coverage, but recovering reliable 3D scale from 2D pixels remains difficult; therefore, achieving stable monocular ranging and speed estimation under practical deployment constraints is still challenging. In this paper, we propose a roadside monocular vision–based method for target ranging and speed measurement. By combining a 3D object detection approach with coordinate transformation, the method outputs real-world target coordinates and speeds in the scene. We conducted several experiments, and the results show that our method can obtain target spatial coordinates and speeds in surveillance settings with reliable performance.

Chen, Ziyi, Lu, Mingfeng, Li, Lan, Pang, Yi, Chen, Yue, Yan, Tianyang, Zhang, Feng, Hu, Weidong

Vision-Based Structural Displacement Measurement Using a Ground-Fixed Laser Reference under UAV Observation

2026-99-2017

11/13/2026

Structural displacement is an important quantity in Structural Health Monitoring (SHM), as it directly reflects the condition and safety of structures. Vision-based measurement methods have been widely studied in recent years, mainly because they allow non-contact sensing and can cover relatively large areas. When these methods are applied to Unmanned Aerial Vehicle (UAV) platforms, however, additional challenges arise. In practical operation, platform motion and attitude changes tend to introduce drift into the measurements, which can noticeably affect the final results. In this study, a displacement measurement approach that combines vision sensing with a laser reference is investigated for both UAV-based and fixed-camera scenarios. A laser source installed on the ground projects a reference spot onto the structural surface, placed close to a multi-circle target. This setup provides a stable reference point that is less affected by platform movement. The displacement is then estimated by tracking the relative motion between the target and the laser spot, instead of relying directly on absolute measurements. With this design, a large part of the motion caused by the platform can be separated, allowing the structural displacement to be expressed in a ground-based coordinate system. The implementation includes several practical steps, such as adaptively selecting regions of interest, performing basic image processing, refining feature locations at the subpixel level, and updating scale factors during operation. Experiments with both UAV and stationary camera setups show that conventional measurements are strongly affected by low-frequency drift, while the laser-referenced results remain relatively stable across different measurement points. According to the Root Mean Square (RMS) analysis, about 77%–95% of the drift caused by platform motion can be reduced under UAV conditions. These results indicate that the method can serve as a practical option for displacement monitoring in UAV-based vision applications.

Li, Zheng, Xu, Junhao, Hua, Yuansheng

2026 6th International Conference on Smart City Engineering and Public Transportation

2026-99-2000

11/13/2026

TOC

Tobolski, Sue

Beyond Static Graphs: A Dynamic Spatiotemporal Transformer Framework for Real-Time Traffic Signal Optimization in Smart City Networks

2026-99-2022

11/13/2026

2222

Lin, Ziyu

Research on the Adaptability and Performance Evaluation Method of DMS and Active Safety Function

2026-99-2025

11/13/2026

As auto-driving technologies advance, the driver monitoring system (DMS) has shifted from a premium option to a standard feature of passenger vehicles. However, the compatibility and coordination between the DMS and the main active safety functions (ASF) of vehicles, such as automatic emergency braking (AEB), forward collision warning (FCW), lane departure warning (LDW) and lane keeping assistance (LKA), have been rarely studied. To fill this research gap, this study first categorized unsafe driving risks into three levels, which serve as a quantitative basis for DMS activation; Then, a novel collaboration model between DMS and ASF is constructed, which outputs dynamic ASF adjustment strategies based on the driver’s status. A multi-dimensional quantitative evaluation indicator system is then constructed to assess the effectiveness of the proposed model and the corresponding strategies. Moreover, controlled tests are performed to verify the model’s effectiveness, and validation tests are performed to confirm that it cannot only enable adaptive optimization of the warning timing and intervention intensity of ASFs, but also balance safety redundancy and driving experience. This study realizes coordination between the DMS and vehicles’ ASFs and provides a reference for optimized design of safety functions of intelligent vehicle safety systems.

Liu, Jiajie, Yang, Guhan, Zhang, Cheng, Ma, Wenbo, Wang, Botong

Multi-Factory Production–Transport Collaborative Scheduling Under Time-Varying Traffic: Traffic Parameterization Embedding and Order-Level Multi-Agent Proximal Policy Optimization (MAPPO) Joint Decision-Making

2026-99-2024

11/13/2026

Multi-factory scheduling presents notable challenges when road congestion exhibits temporal variability, as transport lead times deviate from predefined production plans and schedules deemed feasible at the planning stage may become unfeasible upon dispatch initiation. This study, therefore, addresses the problem through an integrated pipeline of traffic prediction, traffic parameterization, and joint scheduling, which links traffic prediction with scheduling within a unified decision framework rather than treating them as two separate tasks. Link-speed data from the Q-Traffic dataset are utilized to train a Light Gradient Boosting Machine (LightGBM) short-horizon predictor; the predicted speeds are converted into a bounded congestion factor, and a route-wise aggregation method is applied to derive the traffic correction coefficient at the factory-customer-route-time level. Traffic information is incorporated into the scheduler via transport-time adjustments and delivery-related penalty terms, thereby incorporating traffic information without substantially changing the original scheduling structure. At the decision layer, each order is treated as an independent agent, and each scheduling action is defined by the ternary set (factory, route, dispatch time window). The decision layer is trained under the framework of Centralized Training with Decentralized Execution (CTDE) by adopting Multi-Agent Proximal Policy Optimization (MAPPO), a method that mitigates the weak local optima commonly generated by stage-wise planning strategies. Comprehensive experiments, including main performance tests, ablation studies, and robustness analyses, are conducted on small, medium, and large problem instances as well as on low, medium, and high congestion groups. Across all experimental settings, the integration of parameterization and MAPPO joint decision-making achieves a favorable trade-off among total cost, on-time delivery rate (OTD), and average delivery delay, while maintaining stable performance amid traffic congestion fluctuations. Predictor accuracy, reproducible experimental configurations, and summarized results are also reported to support the replication and reuse of the proposed method in traffic-aware production-transport coordination scenarios. In comparison with stage-wise planning and heuristic Earliest Due Date (EDD)-based baselines, the augmented MAPPO policy yields lower overall costs and higher OTD values on large-scale instances. Ablation results further demonstrate that it modulates the learned preferences for routes and time windows in scheduling decisions. Decentralized inference of the proposed model remains in the millisecond range across all tested problem scales, which validates the practicality of the model for rolling-horizon decision support in real-world operations.

Cai, Jiayu

Quantitative and Interpretable Analysis of the Influencing Mechanisms of Ship Pilot Fatigue Based on LightGBM and SHAP

2026-99-2021

11/13/2026

Chuan, Dingkai, Xu, Yanmin, Guan, Hongxu

A Deep Reinforcement Learning-Based Multi-Section Coordinated Variable Speed Limit Control Method for Expressways

2026-99-2009

11/13/2026

This paper proposes a reinforcement learning-based multi-section, coordinated variable speed limit control approach for expressways. The method handles joint speed-limited decision-making at coupled spatiotemporal traffic dynamics across multiple sections and lanes. The traffic state space is constructed based on indicators: lane flow, speed, occupancy rate, number of slow-moving vehicles, and minimum Time-to-collision (TTC). Lane-level speed limits for each control unit are defined as action variables. A weighted reward function is designed to consider operational efficiency, safety, rationality of speed gradient, and control response. The model integrates Convolutional Neural Networks (CNNs) and Gated Recurrent Units (GRUs) to capture spatial correlations and time-varying properties in traffic-state information. In addition, a risk-aware dual-policy output mechanism is introduced to adaptively balance safety-oriented and efficiency-oriented control objectives. Using the Houjie-Xinlian section of the Guangshen Expressway as an example, three control strategies are simulated on the SUMO platform: CGDQN, FCDQN, and an uncontrolled scenario. Experimental results show that the total reward for CGDQN exceeds that of FCDQN. CGDQN reduces vehicle queueing and slow-moving traffic across various scenarios, thereby decreasing the likelihood of traffic accidents. The results demonstrate that the proposed method achieves coordinated multi-section variable speed limit control on expressways under different conditions, and is both feasible and effective.

Zhang, Yuping, Xu, Tian, Ma, Lin, Lin, Siyu, He, Runjing, Yuan, Chenwei

Capacity Evaluation of Manned-Unmanned Integrated Airspace Using a Dual Constraint Mechanism

2026-99-2003

11/13/2026

In the terminal area, the integration of new aircraft (such as electric vertical takeoff and landing aircraft and unmanned aerial vehicle systems) with traditional manned aircraft poses a significant challenge to modern air traffic management systems. To overcome the limitations of traditional macro-delay indicators in identifying local sector risks, this paper constructs a dual-constraint mechanism for sector capacity assessment based on the AirTop simulation platform. This mechanism integrates key factors such as flight conflicts, average aircraft congestion rate, and controller workload to construct a comprehensive performance index. Based on this comprehensive index, this paper constructs a dual-constraint mechanism: on the one hand, it identifies physical abrupt changes in the sector flow efficiency evolution curve; on the other hand, it uses historical safety thresholds from traditional manned aircraft operations for benchmark anchoring. Through these two dual constraints, the safe saturation level of the sector is ultimately determined. Experimental results show that as the UAV integration rate increases from 0% to 30%, the terminal area capacity decreases non-linearly, from 79 flights/hour to 65 flights/hour. When the UAV integration rate is 10%, the mechanism successfully identifies a latent saturation flow of 5 flights/hour and corrects the hourly saturation capacity of the terminal area to 71 flights/hour. Furthermore, this paper applies a multi-sectoral collaborative flow reduction strategy based on set theory to deduplicate flight data, successfully eliminating 22.09% of redundant calculations and effectively avoiding excessive system adjustments caused by spatiotemporal coupling. This fusion method meets the stringent requirements of microscopic security and macroscopic efficiency, providing a solid theoretical foundation and practical technical support for refined capacity management of heterogeneous hybrid airspace in the future.

Wang, Tong, Yang, Lei, Peng, Ziming, Zhang, Yating, Yu, Jiangting

Analysis of Industrial Agglomeration Characteristics in Air-Rail Dual-Hub Regions Based on POI Big Data: Case of Guangzhou

2026-99-2008

11/13/2026

In order to reveal the industrial agglomeration pattern, multi-scale characteristics, and driving mechanism of the air-rail dual-hub regions, this study takes Guangzhou as an example to extract the universal patterns of this region type. Based on POI big data of 9 different types of industries, this study uses kernel density analysis, average nearest neighbor analysis, Ripley’s K function analysis, and spatial autocorrelation analysis to explore the agglomeration characteristics of various industries in the air-rail dual-hub regions. The results show that the industries have a “core-edge” spatial distribution pattern: high-value areas are mainly concentrated around Guangzhoubei Railway Station and Huadu Central Business District, and extend in a belt and bead chain along rail transit and main roads. The overall industries show significant agglomeration, and the intensity is gradient. The consumption-oriented industries are stronger (food and beverage service 0.306, accommodation service 0.331, shopping service 0.338); Culture and education services, enterprises, and sports and recreation services are relatively weak (0.433-0.489); The agglomeration is hierarchical in scale, and the dominant scale is between 1.92 km and 4.48 km, forming a multi-scale structure with the coexistence of “node attachment-mesoscale composite service circle-regionalized cluster superposition”; Industrial POI density is positively correlated with road network density, night light index and population density as a whole, showing the composite driving characteristics of “population support-traffic guidance-vitality enhancement”. The results show that the hub effect of the air-rail dual-hub regions has expanded from the agglomeration around the station to the multi-type composite organization mode of “circle-corridor-group”. The study provides a basis for the guidance of spatial planning in different types and scales of the air-rail dual-hub regions.

Zhang, Ruijie, Ouyang, Jie, Shen, Ziran, Xue, Weining

Influence of Low Stability on Turning Safety of Ro-Ro Passenger Ship

2026-99-2023

11/13/2026

To investigate the safety margin of the Ro-Ro passenger ship (ROPAX) with low stability during turning operations, a four-degree-of-freedom coupled mathematical model was established. The results indicate that during turning maneuvers, the maximum heel angle of the ROPAX vessel significantly exceeds the steady state values specified and calculated by the International Code on Intact Stability 2008 (2008 IS Code). It is noteworthy that this excessive transient heel angle, which exceeds the steady state assessment framework adopted in conventional IMO regulations, often receives insufficient attention in practical engineering and operational evaluations. Nevertheless, its impact on safety is critical. This study provides crucial evidence for evaluating the maneuvering safety margin of the ROPAX vessel and offers a valuable reference for refining stability criteria and operational guidelines for actual navigation.

Wang, Honggui, Li, Yunting, Li, Jinge, Yang, Yong, Wang, Biao, Wang, Xinjian

Optimization of Pedestrian–Vehicle Traffic Flow Organization Design Based on BIM and Simulation Technologies

2026-99-2006

11/13/2026

In order to optimize the traffic organization design under the condition of human-vehicle interaction and solve the problem of a lack of intuitive decision-making basis in the existing scheme, this paper proposes an optimization method for traffic organization design based on BIM and simulation technology. Firstly, BIM modeling and parametric expression of traffic space and organizational elements are completed, ensuring the consistency and operability of design information. Secondly, combined with the simulation technology, the key spatial bottlenecks and index selection of multi-scheme dynamic replication are identified, and the advantages and disadvantages of different design schemes are comprehensively evaluated. Then, through the comparison of multiple rounds of simulation and test of the optimization scheme, the key performance indicators are selected for detailed analysis and evaluation. Furthermore, the TOPSIS method is used to analyze the results of each scheme, and the recommended design scheme is finally determined by considering multiple influencing factors. The experimental results show that the combination of BIM and simulation technology can effectively improve the design selection, identify and solve the spatial bottleneck in the design, optimize the traffic flow organization, and provide an important theoretical basis and practical reference for the traffic organization design under the condition of coexistence of people and vehicles. This study provides a framework for the combination of BIM and simulation for traffic organization design under the condition of coexistence of people and vehicles, which has important reference significance for improving the design selection effect and reducing the operation risk.

Ye, Xiongfeng, Liu, Shaobo

Cooperative Control for Connected Automated Vehicle Platoon under Cut-In Scenarios: A Topology Reconfiguration Approach

2026-99-2018

11/13/2026

This paper proposes a distributed cooperative control framework to address the stability control problem of connected and automated vehicle (CAV) platoons encountering external cut-in vehicles. To maintain platoon cohesion under cut-in scenarios, an active topology reconfiguration approach based on both the predecessor-following (PF) topology and the leader-following (LF) topology is first designed. By designating the first vehicle behind the cut-in vehicle as the new leader and combining with the LF topology, it is ensured that vehicles ahead of the cut-in can access the state information of those behind it, thereby maintaining platoon cohesion. Secondly, a model predictive control system is developed to adapt to the topology changes. Its prediction model, optimization objectives, and safety constraints can all be switched according to the topology, ensuring both platoon cohesion and operational safety. Simulation results demonstrate that the proposed strategy effectively suppresses oscillations in inter-vehicle spacing and speed fluctuations caused by the cut-in vehicle, enabling rapid recovery and smooth control of the platoon, and performs significantly better than static topology strategies. This provides a reliable solution for cooperative platoon control in dynamic traffic environments.

Yao, Yuan, Yang, Lei, Liu, Yafei, Liu, Fan, Sun, Zhanbo

Influence of Joint Load Transfer Capacity on HWD Deflection Response of Airport Cement Pavement and Void Determination

2026-99-2027

11/13/2026

To enhance the scientific rigor and accuracy in detecting voids beneath cement concrete pavements in civil airports, a three-dimensional finite element model consisting of 3 × 3 slabs was established using finite element software based on the Winkler foundation model. The mechanical responses of the slab edge region under loading from the Heavy Weight Deflectometer (HWD) were systematically simulated. In this model, both the load transfer capabilities of various joint conditions — namely good, medium, secondary, and poor — and the configuration of voids beneath the slab were taken into account. The variation patterns of key mechanical indicators, including deflection value and deflection ratio, were analyzed. The results indicate that poorer joint load transfer capacity leads to larger deflection values and deflection ratios at the slab edge, whereas the deflection within the slab interior is less influenced by joint load transfer capacity. The model was validated using measured deflection data from multiple airports, demonstrating strong reliability and applicability. This study provides a theoretical foundation and technical reference for identifying voids beneath airport cement concrete slabs and for supporting maintenance decisions.

Wang, Yuxiang, Ren, Hui, Zhang, Ruya

Correlation Study between Spatial Distribution of POI and Road Network Morphology in Historic Urban Area of Kaifeng Based on sDNA Model

2026-99-2031

11/13/2026

While previous studies have examined road network morphology and POI distribution separately or at single scales, this study introduces a multi-scale analytical framework to investigate their intrinsic correlation in historic urban contexts. Employing the sDNA model and kernel density estimation within ArcGIS, this paper quantitatively analyzes the road network morphology and spatial distribution characteristics of Points of Interest (POI) in the historic urban area of Kaifeng City, and examines their correlation across multiple spatial scales (400 m to 3000 m radii). The results show that: (1) At different spatial scales, the arterial road system in the historic urban area of Kaifeng demonstrates high topological integrity and centrality; (2) The correlation between the road network morphology and POI spatial distribution in the historic urban area weakens with increasing radius. At the same scale, road proximity is more likely to influence the distribution of POI; (3) At the slow-moving scale, the correlation between road network morphology and POI spatial distribution is stronger than at the vehicular scale, and it gradually weakens with increasing radius. These findings reveal a scale-dependent relationship between road morphology and functional agglomeration, suggesting that the vitality core of historic urban areas remains anchored in pedestrian-oriented networks — a theoretical insight with implications beyond the Kaifeng case. The research results can provide a basis for traffic improvement and facility planning in the historic urban area of Kaifeng, and serve as a reference for other historic urban areas. The multi-scale analytical framework demonstrated in this study offers a transferable methodology for diagnosing similar scale-dependent dynamics in diverse historic urban contexts.

Rao, Minglei, Liu, Yanzhong, Zhai, Feifei, Zhang, Yangyang, Zhang, Jingsi

Comprehensive Evaluation and Optimization of Traffic Organization Schemes for Highway Reconstruction and Expansion Based on Traffic Simulation

2026-99-2033

11/13/2026

To address the difficulty in quantitatively evaluating the effectiveness of traffic organization schemes in highway reconstruction and expansion projects, this study proposes an evaluation system integrating traffic safety and operation efficiency. By combining VISSIM simulation with SSAM conflict analysis, this study verifies the effectiveness of the proposed evaluation method through a case study of the Guihua Interchange on the Chengnan Highway. For traffic safety evaluation, a safety risk assessment model is constructed, consisting of four first-level indicators (road, traffic, facilities, and management) and fifteen second-level indicators, along with a four-level risk classification standard. For operational efficiency evaluation, the Level of Service (LOS) and average delay are adopted for quantitative assessment. Simulation experiments are conducted on the three-stage traffic organization scheme for the Guihua Interchange in the Chengnan Highway reconstruction and expansion project. The results show that the comprehensive risk scores of the three-stage scheme are 12, 12, and 13, respectively, all classified as general risk. The peak-hour delay rates of the first and second stages are both lower than 6 s/(veh·km), verifying the feasibility of the temporary ramp and truck diversion strategy. The third-stage simulation indicates that the conflict rate of the east-south ramp reaches 0.58 conflicts/(veh·km) (93.5% of which are lane-changing conflicts). It is suggested to add graphical path indication traffic signs, paint no-lane-changing markings on the inner lanes, and guide ramp traffic flow in advance. The research demonstrates that the proposed evaluation system can effectively support the feasibility judgment, optimization path identification, and dynamic evaluation verification of traffic organization schemes, significantly improving the safety and approval efficiency of reconstruction and expansion projects.

Qin, Lang, Wang, Yue, Chen, Qingyu, Liu, Gang

Key Points and Operational Mechanisms of the IMO Net-Zero Framework and Emission Reduction Cost Analysis for Different Fuels on an 86K Bulk Carrier

2026-99-2029

11/13/2026

In April 2025, the International Maritime Organization (IMO) held the 83rd session of the Marine Environment Protection Committee (MEPC) in London, the United Kingdom. During this crucial meeting, extensive discussions and in-depth negotiations were carried out regarding the mid-term greenhouse gas (GHG) reduction measures under the newly proposed Net-Zero Framework (NZF). The NZF establishes a medium-term regulatory framework featuring a dual compliance structure consisting of basic and direct compliance. Its core components include the Greenhouse Gas Fuel Standard (GFS), the Greenhouse Gas Emissions Pricing (GEP), and Flexible Compliance (FC). Among these, the GFS is positioned as the core regulatory instrument, given that it directly governs the carbon intensity of marine fuels, thereby providing the foundational driver for the industry's transition towards zero or near-zero fuels and technologies (ZNZs). The implementation of this framework will systematically restructure the entire industrial chain of international shipping, including marine power system research and development, new-type ship design and construction, green fuel production, storage, supply, bunkering and certification, seafarers' professional training, as well as daily shipping operation and management. It will inevitably bring about profound and far-reaching impacts on the technological route, investment layout, operational mode, and competitive landscape of the global maritime industry. Against this background, this paper focuses on the NZF, systematically clarifying its formulation background, core institutional components, and practical operational mechanisms. Taking an 86K bulk carrier as the research object, this study carries out a detailed case analysis to reveal the actual challenges and response pathways for shipowners and operating enterprises under the new regulatory system. On this basis, this paper further proposes targeted coping strategies and practical reference suggestions for the shipping industry to adapt to and comply with the upcoming NZF requirements, so as to provide decision support for the sustainable and low-carbon development of the maritime sector.

Li, Zichao, Jian, Yanjun, Zhao, Jiawen, Fu, Xiaming, Dong, Lina, Lu, Chunhui

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