Your Destination for Mobility Engineering Resources

Enter keyword, author, topic...

Announcements for SAE Mobilus

Browse All
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.

Quick Browse

Industries

Content by Type

Recent SAE Edge™ Research Reports

Browse All 177
Wing-in-Ground Effect Vehicles: From Modern Military and Commercial Development to Global Disaster ResponseEPR202501711/24/2025
The wing-in-ground effect (WIG) vehicle represents a significant advancement in aerodynamics and vehicle design, leveraging the ground effect phenomenon to enhance lift and reduce drag when flying close to the surface. This unique capability allows WIG vehicles to achieve higher payloads, longer range, and greater fuel efficiency compared to traditional aircraft, making them an attractive option for modern military and global disaster response applications. Wing-in-Ground Effect Vehicles: From Modern Military and Commercial Development to Global Disaster Response discusses future disaster response, logistics, and military applications for WIG vehicles, including the ongoing development of aerospace and transportation technology. Relavant advancements in materials and propulsion systems holds promise for further enhancing WIG performance and operational range. Additionally, cost-effective and powerful flight computers with various types of mission-enabling sensor suites from the 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 EngineeringEPR20250169/22/2025
Despite growing investments, the widespread adoption and scalable deployment of generative artificial intelligence (AI) remains a challenge due to data trustworthiness, regulatory uncertainty, interpretability, and ethical governance. The need to accelerate automation and maintain the human-in-the-loop demonstrates broader questions of responsibility and transparency. Next-gen AI for Aerospace Engineering investigates the transformative role of GenAI within aerospace engineering, examining its shift from conventional workflows toward more AI-driven solutions in design, manufacturing, and maintenance. It emphasizes GenAI’s emerging ability to automate repetitive mundane tasks, reduce design complexity, and optimize engineering pipelines. The report underscores the need for validation methods that must align AI-generated outputs with physics-informed models, integration with legacy engineering tools (e.g., computational fluid dynamics, finite element analysis, digital twins), and mitigation of algorithmic biases. Click here to access the full SAE EDGETM Research Report portfolio.
Sustainable Circular Future Mobility: Environmental Impact of Next-gen VehiclesEPR20250159/22/2025
The next generation of mobility, driven by shared, driverless, connected, and electrified vehicles, holds strong potential to advance sustainability through lower emissions and improved resource efficiency. However, critical questions remain regarding their true environmental impact, including battery lifecycle management, material consumption, and circular manufacturing practices. Sustainable Circular Future Mobility: Environmental Impact of Next-gen Vehicles explores these unresolved issues, focusing on the shift from internal combustion to electric vehicles, supply chain challenges, regulatory gaps, and the operational realities of sustainable productization. It also critically examines the risks of greenwashing, the need for consistent standards, and the role of intersectoral collaboration—with energy, urban planning, information and communications technologies, and waste management sectors—in building resilient, scalable solutions. The report provides strategic recommendations and 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 FeaturesEPR20250138/13/2025
Advanced technologies that assist the human driver or reduce (or even eliminate) the human driver’s role are becoming increasingly prevalent in new light-duty vehicles used by the general public. These technologies are divided between Active Safety features that monitor the human driver and vehicle motion and act intermittently to mitigate and avoid crashes, and Driving Automation features that assume some or all of the dynamic driving task from the human driver. Both types of technologies have the potential to reduce injuries and save lives by reducing the frequency and/or severity of crashes. Safety Impacts of Active Safety and Driving Automation Features addresses the current capabilities and future potential for Active Safety and Driving Automation features to reduce crash frequency and severity and provides an overview of the state of the industry for both types of features, including current deployments, trends, and anticipated rollouts. Gaps in knowledge, unsettled issues, and suggestions for future research will also be discussed. Click here to access the full SAE EDGETM Research Report portfolio.
Small, Mobile, and Autonomous Agricultural RobotsEPR20250128/13/2025
The automation of labor-intensive picking and planting operations is having an immediate impact in the agricultural indutry. In its simplest form, robotic automation can reduce the labor and soil disturbance while enabling organic soil cover and increasing species diversification through precision approaches to planting, weeding, and spraying. With this, pesticides and fertilizers can be applied in a more targeted way, and with machinery visiting fields more frequently, earlier and more targeted intervention can occur before pests become established. Small, Mobile, and Autonomous Agricultural Robots identifies issues that need to be resolved fo for this technology to thrive, including improving methods of acquiring and labeling training data to facilitate more accurate models for specific applications. It also discusses concepts such as general-purpose mechanical platforms for use as carriers of agricultural automation systems with high stability, positional accuracy, and variable 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 VehiclesEPR20250147/18/2025
Autonomous vehicle motion planning and control are vital components of next-generation intelligent transportation systems. Recent advances in both data- and physical model-driven methods have improved driving performance, yet current technologies still fall short of achieving human-level driving in complex, dynamic traffic scenarios. Key challenges include developing safe, efficient, and human-like motion planning strategies that can adapt to unpredictable environments. Data-driven approaches leverage deep neural networks to learn from extensive datasets, offering promising avenues for intelligent decision-making. However, these methods face issues such as covariate shift in imitation learning and difficulties in designing robust reward functions. In contrast, conventional physical model-driven techniques use rigorous mathematical formulations to generate optimal trajectories and handle dynamic constraints. Hybrid Data- and Physical Model-Driven Safe and Intelligent Motion Planning and 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 IntelligenceEPR20250115/21/2025
Driven by the vast consumer marketplace, the electronics megatrend has reshaped nearly every sector of society. The advancements in semiconductors and software, originally built to serve consumer demand, are now delivering significant value to non-consumer industries. Today, electronics are making inroads into traditionally conservative, safety-critical sectors such as automotive and aerospace. In doing so, electronics—now further propelled by artificial intelligence—are disrupting the functional safety architectures of these cyber-physical systems. Electronics have created the world of cyber-physical systems, raising broader concerns about the broader category of product assurance. Product Assurance in the Age of Artificial Intelligence continues the work of previous SAE Edge Research Reports in examining open research challenges arising from this shift, particularly in automotive systems, as core electronic technologies (e.g., the combination of software and communications) have even 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 MobilityEPR20250095/20/2025
With many stakeholders involved, and major investments supporting it, the advancements in automated driving (AD) are undoubtedly there. Generally speaking, the motivation for advancing AD is driver convenience and road safety. Regarding the development of AD, original equipment manufacturers, technology start-ups, and AD systems developers have taken different approaches for automated vehicles (AVs). Some manufacturers are on the path toward stand-alone vehicles, mostly relying on onboard sensors and intelligence. On the other hand, the connected, cooperative, and automated mobility (CCAM) approach relies on additional communication and information exchange to ensure safe and secure operation. CCAM holds great potential to improve traffic management, road safety, equity, and convenience. In both approaches, there are increasingly large amounts of data generated and used for AD functions in perception, situational awareness, path prediction, and decision-making. The use of artificial 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 ManagementEPR20250085/20/2025
The transportation industry is transforming with the integration of advanced data technologies, edge devices, and artificial intelligence (AI). Intelligent transportation systems (ITS) are pivotal in optimizing traffic flow and safety. Central to this are transportation management centers, which manage transportation systems, traffic flow, and incident responses. Leveraging Advanced Data Technologies for Smart Traffic Management explores emerging trends in transportation data, focusing on data collection, aggregation, and sharing. Effective data management, AI application, and secure data sharing are crucial for optimizing operations. Integrating edge devices with existing systems presents challenges impacting security, cost, and efficiency. Ultimately, AI in transportation offers significant opportunities to predict and manage traffic conditions. AI-driven tools analyze historical data and current conditions to forecast future events. The importance of multidisciplinary approaches and 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 EarthEPR20250054/24/2025
Recent advances are reducing the cost of space launch, high specific power solar cells, and the production of satellite systems. Modular architectures with no moving parts and distributed power systems would minimize assembly and maintenance costs. Together, this may enable space-based solar power to provide decarbonized dispatchable power at a lower cost than equivalent technologies such as nuclear power stations. Space-based Solar Power for Instantaneously Dispatchable Renewable Power on Earth discusses the advances in emerging technologies, like thin film solar cells, reusable launch vehicles, and mass-produced modular satellite systems that would make economic space power feasible. Click here to access the full SAE EDGETM Research Report portfolio.

Latest Journal Issues

Browse All 16
Passenger Vehicle Systems
SAE International Journal of Passenger Vehicle Systems
Electrified Vehicles
SAE International Journal of Electrified Vehicles
Advances and Current Practices in Mobility
SAE International Journal of Advances and Current Practices in Mobility
Sustainable Transportation, Energy, Environment, & Policy
SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy
Transportation Cybersecurity and Privacy
SAE International Journal of Transportation Cybersecurity and Privacy
Connected and Automated Vehicles
SAE International Journal of Connected and Automated Vehicles
Vehicle Dynamics, Stability, and NVH
SAE International Journal of Vehicle Dynamics, Stability, and NVH
Transportation Safety
SAE International Journal of Transportation Safety
Alternative Powertrains
SAE International Journal of Alternative Powertrains
Commercial Vehicles
SAE International Journal of Commercial Vehicles
Passenger Cars - Mechanical Systems
SAE International Journal of Passenger Cars - Mechanical Systems
Passenger Cars - Electronic and Electrical Systems
SAE International Journal of Passenger Cars - Electronic and Electrical Systems
Fuels and Lubricants
SAE International Journal of Fuels and Lubricants
Materials and Manufacturing
SAE International Journal of Materials and Manufacturing
Aerospace
SAE International Journal of Aerospace

Recent Books

Browse All 633
Composite Materials Handbook Volume 5 - Revision BR-4608/27/2026
The fifth volume of this six-volume compendium publishes technical guidance and properties on ceramic matrix composite material systems. The selected guidance on technical topics related to this class of composites includes material selection, processing, characterization, testing, data reduction, design, analysis, quality control, application, case histories, and lessons learned of typical ceramic matrix composite materials. Volume 5, which covers ceramic matrix composites, supersedes MIL-HDBK-17-5 of June 17, 2002. The Composite Materials Handbook, referred to by industry groups as CMH-17, is an engineering reference tool that contains over 1,000 records of the latest test data for polymer matrix, metal matrix, ceramic matrix, and structural sandwich composites. CMH-17 provides information and guidance necessary to design and fabricate end items from composite materials. It includes properties of composite materials that meet specific data requirements as well as guidelines for design, analysis, material selection, manufacturing, quality control, and repair. The primary purpose of the handbook is to standardize engineering methodologies related to testing, data reduction, and reporting of property data for current and emerging composite materials. It is used by engineers worldwide in designing and fabricating products made from composite materials.
July 2026 AMS IndexAMSJULY-20267/22/2026
Metallic Materials Properties Development and Standardization (MMPDS) Handbook - 2026 - Volume IB-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 IIB-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 EditionR-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 FuelsR-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 - 2026ASIN20262/25/2026
This valuable resource lists all Aerospace Standards (AS), Aerospace Recommended Practices (ARP), Aerospace Information Reports (AIR), and Aerospace Resource Documents (ARD) published by SAE. Each listing includes title, subject, document number, key words, new and revised documents, and DODISS-adopted documents. AMS Index - Now Available!
Business Reliability Growth for Automotive Engineering, Volume 4R-5522/17/2026
In a world where every business process is under pressure to perform faster, safer, and more reliably, this book delivers a powerful roadmap for sustained operational excellence. Centered on the proven methodology of Design of Experiments (DOE), it shows how organizations can move beyond reactive problem-solving to systematic reliability growth. From well-defined standard operating practices to management-level decision-making, the book connects strategy, data, and execution to create repeatable, measurable results across the enterprise. Readers are guided through practical, real-world applications of DOE, from selecting the right factors and levels to executing robust experiments, analyzing outcomes, validating solutions, and continuously monitoring performance. Each chapter translates complex statistical and engineering concepts into actionable business value, helping teams improve quality, reduce waste, and increase return on investment. Key capabilities explored in this book 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 FuelsR-5471/22/2026
As global energy demands rise and environmental challenges intensify, the aviation industry faces a critical need to redefine how it powers the skies. Fundamentals of Sustainable Aviation Fuels presents a comprehensive, research-driven exploration of the transition from fossil-based fuels to renewable alternatives that promise to reshape the future of air transportation. This book bridges the gap between academic knowledge and industrial application, offering a detailed overview of the science, technology, and policy driving the adoption of Sustainable Aviation Fuels (SAFs). From understanding feedstocks and conversion pathways to evaluating production technologies, emissions performance, and life-cycle impacts, the text equips readers with a holistic understanding of SAFs within today’s global energy landscape. Across five insightful chapters, readers will find a clear roadmap: the evolution and importance of SAFs; production methods and technological foundations; environmental 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 VehiclesR-5591/20/2026
The convergence of Advanced Driver Assistance Systems (ADAS) and connected vehicle technologies is ushering in a transformative era of automotive innovation—one that is fundamentally enhancing vehicle safety, efficiency, reliability, and the overall driving experience. SAE International’s Dictionary of ADAS and Connected Vehicles stands as the definitive reference for this rapidly evolving domain, meticulously compiled to clarify and standardize the language shaping modern mobility. Inside, readers will find clear, authoritative definitions encompassing the full spectrum of technologies that enable connected and automated driving—including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-everything (V2X) communication systems. This comprehensive resource translates complex engineering terminology into accessible language, enabling engineers, researchers, policymakers, educators, and enthusiasts to share a common technical foundation. Reflecting the latest 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

Browse All
Assessment Model for Fitness for Work of Construction Personnel in Expressway Bridge Engineering Projects2026-99-15099/11/2026
To mitigate safety risks inherent in highway bridge construction, this research establishes a practical framework for assessing workers’ fitness for work. Using grounded theory, we analyzed interview records and documented accident cases through systematic coding, identifying critical indicators spanning physiological states, safety training effectiveness, and atypical behavioral markers. Rather than relying on single-method approaches, we combined Delphi expert consultation with entropy weighting to capture both professional judgment and data-driven variance, thereby reducing bias while preserving information richness. The resulting assessment protocol enables quantifiable classification of workers into distinct risk tiers. Implementation at the Zhangjinggao Yangtze River Bridge demonstrated the system's discriminatory power through field data collection and direct behavioral monitoring, successfully segmenting the workforce into low-, medium-, and high-risk categories. Results suggest the tool functions effectively as a pre-employment screening mechanism, allowing project managers to intercept potentially unfit workers before they enter hazardous work zones, consequently lowering the incidence of human-factor accidents.
Wu, Zhongguang, Dai, Junping, Ruan, Jing, Shi, Yonglong, Yuan, Zhenzhong, Hao, Jiatian
Study on Rapid Formation Generation Method for Multi-UAV Swarms2026-99-14219/11/2026
This paper presents a generalizable geometric framework for rapid on-demand generation of multi-UAV formations with arbitrary 2D geometries and user-specified scalable scales. First, vertices, edge intersections and edges are extracted from a user-defined formation template to enable parametric description of both simple and composite formation geometries. Second, boundary interpolation, edge expansion and recursive internal expansion are integrated to synthesize hierarchical multi-layer UAV deployment point sets under a controllable expansion ratio. Third, a geometric distortion metric is proposed to optimize UAV node indexing and formation reconstruction while preserving inter-node topological consistency. Algorithmic derivations, complexity analysis and simulation assumptions are further elaborated. Simulation results verify that the proposed method preserves geometric fidelity of target formations while delivering superior scalability and spatial coverage, rendering it well-suited for emergency transport, aerial surveying and low-altitude cooperative missions in dense urban environments.
Fu, Mingyi, Zeng, Guoqi, Gu, XinZhu, Wang, Jia
Research on Planting Concrete Preparation and Alkali Reduction Technology2026-99-15189/11/2026
Planting concrete has drawn much attention due to its great potential in highway slope protection and ecological restoration. However, its practical application has been limited as its highly alkaline environment imposes severe restrictions on the germination of plant seeds and the growth of seedlings. To address this key issue, this paper conducted a systematic study on planting concrete preparation and alkali reduction technology. First, planting concrete samples that meet the basic physical and mechanical property requirements are prepared by optimizing the raw material ratio, mixing, molding, and curing processes. On this basis, the post-molding concrete samples are soaked in calcium superphosphate solution, so that the phosphate ions in it can have chemical reactions with the free calcium hydroxide in the concrete to make insoluble calcium phosphate salts, thus realizing chemical alkali reduction.
Liu, Ying, Yang, Wanting, Ma, Lijie
Emotional Impacts of Manual and Assisted Driving Modes under Varying Time Pressures: A Scenario-based Simulation Study2026-99-15089/11/2026
Emotion as a critical psychological variable in driving behavior has been extensively confirmed to exert a profound influence on traffic safety. With the advancement of autonomous driving technologies, the application value of emotion regulation mechanisms in intelligent transportation systems is gaining importance, given their proven impact on reducing unsafe driving tendencies and improving human-machine interaction quality. However, systematic research on the mechanisms underlying emotional variation across different driving modes remains relatively scarce. This study developed a questionnaire based on the Chinese version of the Driving Anger Scale (DAS), incorporating 19 traffic scenarios and corresponding video stimuli, to examine the impact of manual and assisted driving on driving anger under varying levels of time pressure. In addition, the moderating effects of individual factors such as age and education were analyzed. Descriptive statistics, independent samples t-tests, and one-way ANOVA were applied to 113 valid responses to construct a three-dimensional analytical framework involving driving mode, time pressure, and demographic variables. The results indicate that under high time pressure, assisted driving systems significantly reduce drivers' anger levels in typical delay-related scenarios compared with manual driving. Age is identified as a key moderating factor influencing emotional responses. This research provides theoretical support for the development of emotion-aware driving intervention systems and offers empirical evidence for the formulation of future strategies for driving emotion regulation.
Zhang, Tingjia, Li, Ruiheng, Zhu, Tong
2025 5th International Conference on Logistics System, Traffic and Transportation (LSTT 2025)2026-99-15009/11/2026
TOC
Tobolski, Sue
Numerical Calculation of The Ice-Breaking Resistance of the Icebreaker2026-99-15179/11/2026
This study investigates the governing characteristics of ice resistance encountered by icebreakers operating in multi-year ice regions, with particular emphasis on the effects of bow truncation length, vessel speed, and ice thickness. A numerical simulation framework was developed using the finite element platform LS-PrePost to reproduce ice bending, failure, and ship–ice interaction throughout the icebreaking process. The numerical predictions were subsequently validated against physical model test data. The results indicate that ice resistance exhibits an increasing trend as the bow truncation length, navigation speed, and ice thickness increase. The ice resistance of different bow truncation lengths in the multi-year ice area is different. By truncating the model ship at different positions from the bow and analyzing the ratio of the ice resistance of the truncated models to that of the full-scale model, researchers can better understand the effects of bow size. This can provide a theoretical basis for conducting ice resistance tests with truncated model ships in a limited-scale ice water tank, and has certain practical value for the design and optimization of the icebreaker’s hull lines.
Liu, Yanwei, Zhang, Xiufeng, Yu, Yingjie, Wang, Lucai, Zhao, Weihang
Experimental Analysis of Tube Temperature and Heat Transfer Performance of L-Shaped Gravity Heat Pipes2026-99-15119/11/2026
Gravity heat pipes achieve efficient energy transfer through the evaporation and condensation of their internal working fluid, which steadily conducts underground heat to the surface and thereby provides a continuous and stable heat source for road pavements in winter. Considering the snow and ice melting demand of road surfaces in winter, this paper establishes an indoor environmental simulation experimental platform to systematically investigate the influence laws of different working fluids on the start-up temperature, start-up pressure, heat transfer power, and other key performance indicators of L-shaped gravity heat pipes. Through experimental research and analysis, it is revealed that heat pipes with R-134a and R245fa working fluids can operate stably at a shallow geothermal temperature of about 25 °C, while the acetone working fluid heat pipe operates unstably under this condition. The heat pipe filled with R-134a working fluid achieves the maximum heat transfer power under shallow geothermal conditions, followed by the heat pipe filled with R245fa. Although the heat transfer power of the acetone-filled heat pipe is generally relatively low, its heat transfer power increases most significantly with the rise of the evaporation section temperature. Under low-temperature conditions, the thermal conductivity of the evaporation section increases with the rise in the heating temperature of the evaporation section, while that of the condensation section decreases with the increase in the heating temperature of the evaporation section. Through experimental research and comparative analysis, this paper deeply explores the application potential of gravity heat pipe technology in green highway construction, and evaluates the feasibility and economic benefits of its engineering implementation, which provides a scientific basis and engineering guidance for the selection of green energy in future infrastructure construction.
Wang, Zhen-kun, Yuan, Zhi-ming, Wang, Kang, Zhang, Wen-jun, Wu, Xiang-song, Liu, Guang-bo
Train Delay Reduction Approach based on a Virtually Coupled Trains Following Model with Timetable Recovery Process: A Case of High-Speed Rail2026-99-15169/11/2026
One challenge in railway operation is how to achieve high levels of punctuality and reliability. However, especially in peak hour operation, a high volume of train traffic will affect timetables, which are more sensitive to the increase in travel time. The concept of virtual coupling has been introduced for controlling train movement mainly to increase capacity. As the operation under virtual coupling requires a short separation distance between trains, it might be applied to reduce the delay and recover the train timetable. However, there is no approach proposed detailing how the coupling is applied to reduce delay. In this paper, the virtual coupling state movement approach based on a vehicle following model with the coupling conditions determined to couple a group of trains for reducing or preventing secondary delay is proposed. The train operation under the proposed approach is simulated in MATLAB software, then applied to the hypothetical case, High-speed line, Bangkok - Nakhon Ratchasima, Thailand. The delay analysis is performed, and the waiting probability is determined to prove the effectiveness of the proposed approach. The simulation results show that trains will be virtually coupled with their front train as a form of train convoy when they cannot proceed at the ideal speed. Thus, operating train movement based on the proposed approach can reduce secondary delay and bring a train to arrive on time compared to the operation under the moving block control.
Chansong, Sukanya, Ketphat, Naphat
Conceptual Design of Steel Shell-UHPC Composite Pylon for Large-Span Suspension Bridges2026-99-15139/11/2026
With the rapid development of the transportation industry, heavy-duty traffic has become extremely common, particularly in some coastal port cities where the presence of container terminals leads to generally high vehicle axle loads. In these regions with an advanced transportation industry, large-scale cross-sea bridges are often required to ensure transport efficiency. However, conventional long-span bridge types, such as cable-stayed bridges and suspension bridges, face challenges in meeting the demands of heavy-duty traffic due to limitations imposed by the self-weight of pylons. In response, this paper proposes a prefabricated steel shell–ultra high performance concrete (SS–UHPC) composite pylon composed of basic SS–UHPC units, aiming to enhance both the load-carrying efficiency and seismic performance of the structure. A conceptual design of the SS–UHPC composite pylon was developed based on a super-long-span suspension bridge with a main span of 2180 m, and a comparative analysis was carried out against a conventional steel shell–normal concrete (SS–NC) composite pylon. The results show that, owing to the higher strength-to-self-weight ratio of UHPC, the SS–UHPC composite pylon achieves a 42.4% reduction in self-weight compared to the SS–NC composite pylon. Under the most unfavorable load condition, the axial force and transverse bending moment at the pylon base are reduced by 13.79% and 6.24%, respectively. Under maximum seismic load, the axial force and transverse bending moment at the base decrease by 14.12% and 28.92%, respectively, demonstrating improved load-carrying efficiency and seismic performance of the pylon. Although the life-cycle cost of the SS–UHPC composite pylon is higher than that of the SS–NC composite pylon, its superior mechanical behavior sufficiently offsets the cost difference. In conclusion, the superior mechanical behavior of the SS-UHPC composite pylon makes it better suited for application in long-span bridges subjected to heavy-duty transportation loads.
Chen, Jing Li, Liu, Yong Jian, Peng, Hong Bo, Sun, Li Peng, Yang, Ze Hong
Dimensional Adaptability and Traffic Organization Analysis of Ships in Group Lockage2026-99-15109/11/2026
Aiming at the technology of electric intelligent working boat towing 4 ships in group lockage during the construction period of the Gezhouba Shipping Capacity Expansion Project, this paper, starting from ship dimensions, conducts an adaptability analysis on electric intelligent working boat towing ships in group lockage for all ships passing through Gezhouba No. 1 and No. 2 Ship Locks throughout 2024, based on the two-dimensional packing model, ship lock chamber scheduling model and algorithms, navigation scheduling rules and safety management regulations, the results show that ships unsuitable for being towed in group lockage through Gezhouba No. 1 Ship Lock account for approximately 26% of the total number of ships passing through it, while those unsuitable for being towed in group lockage through Gezhouba No. 2 Ship Lock account for approximately 57% of its total passing ships. Meanwhile, ships passing through the three Gezhouba ship locks on a specific day are selected, and an adaptability analysis on the dimensional suitability of electric intelligent working boat towing these ships in group lockage is carried out under the scenario where these ships only pass through Gezhouba No. 1 and No. 2 Ship Locks. The results show that the number of ships with suitable dimensions for group lockage accounts for the majority of the ships passing through the locks on a selected specific day. On this basis, combined with the operation modes of Gezhouba No. 1 and No. 2 Ship Locks, an analysis is carried out on the traffic organization, potential risks, corresponding countermeasures, and the required quantity of electric intelligent working boats for towing ships in group lockage, targeting the three main collaborative operation modes. The results can provide a basis for the future practical application of electric intelligent working boat towing ships in group lockage during the construction and operation periods of the Gezhouba Shipping Capacity Expansion Project.
Huang, Shaowen, Yang, Xi, Wang, Jian
Study on Route Planning Method of Variable-Configuration Vehicles Considering Mode Decision2026-99-15019/11/2026
The form changes of vehicles directly affect their driving performance, terrain adaptability, and motion efficiency. Conventional path planning techniques are unable to address the unique needs of irregularly shaped vehicles. Consequently, a hierarchical path planning algorithm that takes configuration changes into account is introduced. By introducing a pattern decision-making mechanism, the path planning process is divided into multiple levels. According to the task requirements and environmental conditions, the vehicle configuration is dynamically selected, and the driving path is optimized for the driving characteristics under different configurations, thereby fully utilizing the adaptability and through capability of the vehicle.
Chen, Zixuan, Pi, Dawei, Li, Guangda, Zhou, Yulin
Effect Evaluation of Emergency Barrier-free Blocking Methods in Highway Tunnels Based on Visual/Driving Behavior2026-99-15319/11/2026
To address the lack of safe and effective on-site vehicle blocking and control methods in the event of fires or other emergencies in extra-long tunnels — which can significantly reduce traffic safety risks and prevent secondary accidents — this study proposes a novel barrier-free light–smoke curtain interception method. The method integrates conventional traffic safety warning facilities (gantry-mounted variable message signs and audio–visual alarms) with two light–smoke curtain interception images to form a composite early-warning and interception system. Driving simulation experiments were conducted to comprehensively evaluate its warning effectiveness, interception performance, and operational safety in comparison with methods employing only traditional warning facilities or light curtain images. Furthermore, field drills were performed to validate its real-world applicability and interception effectiveness under both daytime and nighttime conditions. The main findings are as follows: 1) The fixation ratio and interception success rate associated with the proposed method were significantly higher than those of the other two methods, demonstrating enhanced visual attention and superior warning and interception performance. 2) The maximum deceleration observed with the proposed method was lower than that of the light curtain–only method and did not trigger emergency braking, thereby indicating high operational stability and driver comfort. 3) In field drills, after activation of the interception equipment, only one and two vehicles entered the tunnel under daytime and nighttime conditions, respectively, and full control of on-site vehicles was achieved within two minutes without any traffic accidents, verifying the system’s rapid response and effective safety assurance.
Shi, Mingjun, Li, Shicao, Wang, Haohuan, He, Qifei, Che, Zhengzhang, Li, Yanbo
Nc5-PCS Based Heterogeneous Point Cloud Matching for Roads2026-99-15339/11/2026
Point cloud registration represents a fundamental task in geospatial informatics and 3D computer vision, aiming to align heterogeneous point clouds through rigid transformation estimation. While Super-4PCS serves as an efficient coarse registration method, it exhibits limitations when handling large-scale datasets, planar-distributed point clouds, and scenarios with unknown scale differences. To overcome these challenges, this paper proposes the Nc-5PCS (Neighborhood-constrained 5-Point Congruent Sets) algorithm. Nc-5PCS first performs approximate scale estimation through concavity-convexity similarity analysis within coarse overlap regions, addressing the inherent scale limitation in 4PCS-based approaches. Subsequently, the algorithm employs 3D Harris feature point extraction to significantly reduce data volume while preserving critical geometric characteristics. The core innovation lies in designing a non-coplanar 5-point basis with a corresponding hash-based retrieval mechanism, effectively resolving the feature degradation problem caused by coplanar 4-point bases. Furthermore, normal vector angular constraints are incorporated to enhance consensus evaluation during correspondence selection, substantially improving registration accuracy. Experimental validation demonstrates that Nc-5PCS achieves a point-to-point RMS error of ≤ 0.227 m, outperforming Super-4PCS to provide superior initial alignment for subsequent ICP refinement.
Liu, Lei, Yu, Keguang, Li, Xinyi, Sun, Guangde, Zhao, Xinyuan, Zhu, Dongni, Fan, Yabo, Guo, Shihao
A Maritime Occluded Ship Detection and Tracking Method Based on Improved YOLOv8 Fused with AIS Trajectory2026-99-15499/11/2026
Typical maritime monitoring scenarios are usually constrained by factors such as multi-scale ship density, frequent motion overlap, and limited viewing angle of shore-based cameras. These challenges often lead to trajectory interruptions and identity mismatches in target detection and multi-target tracking tasks. In order to solve these problems, this study proposes a ship occlusion detection and tracking method based on the improved YOLOv8 model and further integrates an automatic identification system (AIS) trajectory reasoning. The method builds a unified perception framework with enhanced detection architecture, multi-source data fusion, and behavioral reasoning capabilities. First, in the target detection module, the improved SEConv structure is introduced into the YOLOv8 trunk network to address challenges caused by small-scale variations and severe occlusion in maritime scenes. The ReLU activation function in SEConv is replaced by the Swish activation function to enhance the nonlinear feature representation. In addition, the optimized SEConv is embedded in the C2f structure, and the convolutional block attention module (CBAM) attention mechanism is introduced to enhance the sensitivity of the model to the occlusion area. Next, for multi-target tracking, ByteTrack is used as the basic tracking framework. AIS trajectory data is introduced as auxiliary input to compensate for trajectory losses caused by occlusion. Finally, experimental results on the SeaShips public dataset and the self-built occlusion reference dataset show that the improved YOLOv8 detector achieves stable mAP gains in mild, moderate, and severe occlusion scenarios. The AIS enhanced tracking system improves the multi-target tracking accuracy (MOTA) and identification F1 score (IDF1) by about 6.3% and 8.1%, respectively, and the average occlusion reconstruction error is controlled within 1.4 seconds. The proposed method effectively enhances the perception ability of ships in complex occlusion environments and verifies the feasibility and superiority of the strategy of combining visual detection with AIS data assistance.
Guan, Keping, Chen, Miao, Zhou, Yue
Design and Analysis on a Traction-type Power-assisted Follow-up Vehicle for Emergency Rescue2026-99-15479/11/2026
To address problems in China’s emergency rescue scenarios—such as limited functionality, insufficient mobility, poor adaptability to complex terrain, the labor-intensive nature of manual carrying, and the lack of flexibility of fully automatic carts—a traction-type emergency rescue power-assisted follow-up vehicle was designed and developed. With the core design goals of “lightweight, high mobility, and human-machine collaboration”, this power-assisted follow-up vehicle has multiple advantages. At the structural level, it supports rapid folding and unfolding, enabling convenient operation and adaptation to transportation needs in various emergency rescue scenarios. In terms of material selection, it balances strength and lightweight properties, and its key components possess anti-cutting and flame-retardant capabilities, allowing adaptation to the harsh environment of emergency rescue. The power system adopts modular replaceable batteries and is equipped with a high-performance control unit, motor, and shock-absorbing suspension design. This enables normal operation in a variety of complex terrains. The control system is centered on human-machine collaboration. It features simple operation and automatic adjustment of operating status, effectively reducing the operational burden and physical exertion of rescuers. Meanwhile, it supports the master-slave expansion function, allowing flexible switching from a two-wheel structure to a four-wheel structure to meet diverse rescue needs such as material transportation and casualty transfer. This power-assisted follow-up vehicle can effectively solve the material transportation problem in the “last few kilometers” of emergency rescue.
Xu, Jiang, Hou, Yumeng, Yang, Han
Research on Passenger Flow Prediction of Urban Rail Transit Based on Grey Improvement Model2026-99-15649/11/2026
In recent years, China's urban rail transit sector has undergone rapid expansion, with passenger demand consistently increasing. Accurate passenger flow forecasting is essential for ensuring efficient and safe metro operations. This paper takes Nantong Metro Line 1 as a case study and applies an optimized forecasting approach that integrates a grey metabolism model with the Holt double-parameter exponential smoothing method. Based on an analysis of Automated Fare Collection (AFC) data from March 2023 to February 2024, passenger flow on this line demonstrates a clear linear growth trend, which aligns well with the assumptions of the grey metabolism model. The results indicate that the optimized grey metabolism model not only significantly enhances prediction accuracy but also greatly reduces the variance ratio, demonstrating high reliability in forecasting outcomes. This improved methodology provides a more robust tool for metro operators in planning services, managing capacity, and optimizing resource allocation.
Fan, Fan, Zhao, Zeheng, Zhang, Jin, Ma, Junhao, Qian, Beiyue
Study on Life Cycle Carbon Emissions of Light Commercial Vehicles2026-99-15399/11/2026
In alignment with China’s national strategic objectives of “carbon peaking and carbon neutrality”, this study aims to pinpoint key greenhouse gas emission sources across the full life cycle of light commercial vehicles. A specific model of gasoline-powered truck is selected as the research subject for this investigation. Using a Life Cycle Assessment (LCA) framework and strictly following relevant international and national standards, this study constructs a three-stage accounting model covering the “raw material– manufacturing–use” process. This model quantifies the vehicle’s carbon emissions across all life stages and provides a detailed breakdown of their composition. Over 90% of the truck’s total carbon footprint stems from its use phase alone, highlighting this stage as the primary emission source. Within the use phase, the well-to-wheel emissions of gasoline are the main emission source. During the materials acquisition and processing stage, the smelting processes of steel and aluminum (including aluminum alloys) are the primary contributors to carbon emissions. The findings of this study can provide data support and technical references for commercial vehicle enterprises in low-carbon product design, green supply chain management, and the formulation of industry carbon emission standards.
Hu, Xiaona, Li, Jing, Chen, Ke, Cui, Chen
Analysis of Differences Between the Current CLTC and China’s Current Traffic Operation Characteristics2026-99-15419/11/2026
With the significant increase in the ownership and market share of new energy vehicles, the current characteristics of China’s traffic operation have undergone remarkable changes compared with those before 2020. This paper focuses on a systematic study of the differences between the current China Light-duty Vehicle Test Cycle (CLTC) and the current traffic operation characteristics. Firstly, the data are derived from the actual on-road operation data of nearly 400 new energy vehicles collected during 2020-2025. Based on this, a comparative analysis framework is established from two dimensions: differences in variable characteristics and differences in test energy consumption. The results show that due to the substantial rise in new energy vehicle ownership and market share, the maximum speed on roads has increased significantly, and the acceleration and deceleration have become more intense. The significant changes in traffic operation characteristics have further widened the deviation between the energy consumption tested under the existing CLTC and the actual energy consumption. Comprehensive research indicates that the increased market penetration of new energy vehicles has brought about obvious changes to the traffic operation characteristics formed during the era dominated by traditional fuel vehicles. Therefore, launching a new round of revision work on the CLTC is of great practical significance for promoting the high-quality development of the new energy vehicle industry in the future.
Yu, Hanzhengnan, Cao, Xiaofei, Zhang, Hao, Yi, Junyu, Zhang, Yongren, Wang, Yang, Wang, Chuanjin, Liu, Te, Ma, Dehui
Research on an Evaluation Method and Application of Autonomous Vehicles in Traffic Flow Environment2026-99-15629/11/2026
Traffic flow environment testing is indispensable in the research and evaluation process of intelligent vehicles. However, the current vehicle evaluation systems mostly focus on simple dynamic scenarios and lack a comprehensive assessment of vehicle performance in complex traffic flow environments. In view of this, this paper constructs a multi-dimensional comprehensive performance evaluation system for vehicles in traffic flow environments. Firstly, based on the randomness and dynamics of traffic flow, four core evaluation dimensions covering safety, comfort, efficiency, and economy are constructed. In terms of security, the collision time and Predicted Safety Metrics are adopted. This enables the dual quantification of immediate collision risks and dynamic obstacle avoidance capabilities. The comfort evaluation focuses on the impact of vibration frequency on the human body and constructs a graded quantitative index. Efficiency and economy evaluation models are built through time cost and energy consumption cost. The verification is carried out under different traffic flow scenarios, and the final results demonstrate the consistency between the evaluation method of this paper and the expert evaluation method, thereby verifying the rationality of the evaluation system presented in this paper.
Wang, Guangyu, Song, Shiping, Zhang, Cheng, Qu, Ge, Yu, Xiaojun
Emergency Rescue Resource Allocation Model and Reasoning Prediction Method for Expressway Reconstruction and Extension2026-99-15489/11/2026
During expressway reconstruction and extension, when a traffic accident occurs, how to make a scientific and reasonable allocation of emergency resources is the premise and basis for efficient rescue. In view of the reconstruction characteristics and the complexity of emergency rescue, the number of casualties, the damage degree of road facilities, the number of damaged vehicles, the range of hazardous chemicals, the size of the fire, and the traffic order were used as the accident attribute indexes to build a historical accident set (case database). The allocation of emergency rescue resources was predicted using case-based reasoning techniques. Also, the corresponding reasoning prediction method was proposed. The research shows that this model can accurately predict the demand for emergency rescue resources during the period of expressway reconstruction and extension, which has good availability and operability, and provides methodological and modeling support for the emergency rescue resource decision system.
Ran, Jin, Zhan, Shiyang, Kadir, Ahmetjan, Ma, Jiarui, Dai, Xiaomin
Analysis of Traffic Capacity at the Intersection of Xiyou Road and Qianshan Road in Hefei City2026-99-15519/11/2026
With the advancement of urbanization and the popularization of automobiles, the traffic load on urban roads is becoming increasingly heavy, resulting in many traffic problems. Road intersections serve as crucial linchpins in the urban transportation grid, wielding considerable influence over the overall traffic capacity of a city’s road network. Enhancing intersection efficiency and cutting down on delays stand at the heart of tackling urban congestion challenges. This study zeroes in on the crossroads where Xiyou Road intersects with Qianshan Road in Hefei City. Employing hands-on observation and photographic documentation, the research examines traffic flow and signal configurations during the peak demand period (7:30-8:30). The analysis evaluates traffic capacity and utilization rates for through, left-turn, and right-turn lanes at this intersection. Findings reveal that the right-turn lane at the southern entrance and the left-turn lanes at both northern and eastern entries show relatively low saturation levels, while the saturation of other lanes is greater than or close to 1. Therefore, this intersection does not have sufficient capacity. The actual traffic operation at the intersection, particularly during peak traffic times, is analyzed to identify the reasons for congestion Finally, improvement plans for optimizing traffic organization at intersections are proposed, such as optimizing signal timing schemes and transforming traffic channelization. Simulation analysis using VISSIM shows a 9.34% reduction in total intersection parking time, a 34.26% decrease in average queue length, and an 8.12% reduction in average vehicle delay. These results provide a reference for future optimization work, including intersection signal timing and channelization.
Wang, Yanmei, Wang, Chen, Fu, Ziyue, Meng, Xianglong
Safety Analysis of Collision Avoidance for Semi-Autonomous Navigation Ship Based on STPA-CREAM2026-99-15549/11/2026
With the continuous improvement of ship intelligence, more intelligent onboard navigation equipment and intelligent navigation systems are used to assist in improving navigation efficiency. This study takes semi-autonomous navigation ships as research objects and adopts System-Theoretic Process Analysis (STPA) to model the complex interaction relationships of semi-autonomous navigation encounter scenarios and identify and analyze potential risks. To address the deficiency of STPA in human factors analysis capability, the Cognitive Reliability and Error Analysis Method (CREAM) is introduced to analyze human factors in semi-autonomous navigation. Finally, based on the results of the STPA-CREAM analysis, recommendations are provided to improve the safety of semi-autonomous navigation.
Zhang, Xiaojie
ASTDGCN: An Adaptive Spatial-Temporal Diffusion Graph Convolutional Network for Traffic Forecasting2026-99-15839/11/2026
Precise traffic flow prediction functions as the fundamental cornerstone for the efficient, safe, and reliable operation of intelligent transportation systems (ITS). It not only provides data-driven support for key applications, for instance, real-time traffic signal regulation, proactive congestion mitigation, and personalized route optimization, but also exerts a critical effect on reducing traffic accidents and improving overall urban travel efficiency. However, the traffic system belongs to a complex system, with spatio-temporal dynamics that are both intricate and variable, ranging from predictable fluctuations during morning and evening peak hours to localized propagation effects caused by accidents, as well as seasonal variations and significant nonlinear characteristics. These factors collectively pose substantial challenges to building accurate and reliable prediction models, creating a long-standing technical bottleneck in this field. With the aim of solving the dilemma that existing methods are hardly able to capture traffic flow’s spatio-temporal dependence effectively, we advance an adaptive spatial–temporal diffusion graph convolutional network (ASTD-GCN) for a traffic flow prediction model that integrates adaptive graph learning, diffusion convolution, and bi-directional long short-term memory network (Bi-LSTM) with attention mechanism. The model dynamically constructs the correlation between the nodes of the transportation network through the adaptive graph learning module and accurately describes the spatial topology. The diffusion convolution module realizes multi-order spatial information diffusion based on graph structure, which realizes the effective extraction of the traffic flow’s spatial dependence features. The Bi-LSTM module incorporating the attention mechanism captures the historical and future context information of traffic flow simultaneously through the bidirectional loop structure and the temporal attention mechanism, and strengthens the key time step features. Experimental results on -world traffic datasets PEMS03, PEMS04, PEMS07, and PEMS08 indicate that our proposed model exhibits better predictive precision in traffic flow forecasting tasks than baseline counterparts.
Li, Sumin, Gao, Yina, Zhu, Hongnian
Adaptive MPC Path Tracking Control for Autonomous Vehicles2026-99-15709/11/2026
This work introduces a Model Predictive Control (MPC) path tracking controller, which is developed to boost robustness, tracking precision, and vehicle stability when navigating high-speed and high-curvature driving scenarios. First, a 3-degree-of-freedom (3-DOF) dynamic model of the vehicle is established to serve as a reference. Next, a linear time-varying MPC control algorithm is formulated, with constraints on yaw rate, lateral velocity, and road boundary conditions taken into account; a comprehensive performance metric that balances tracking accuracy and control smoothness is also defined. Third, the time-domain parameters of the MPC framework are optimized using an improved genetic algorithm. Finally, the effectiveness and accuracy of the proposed controller are validated via co-simulation experiments conducted on the Matlab/Simulink and Carsim platforms. Simulation results demonstrate that the controller exhibits excellent robustness: the peak lateral tracking error is only 0.05 m on high-friction roads and 0.12 m on low-friction roads, with a maximum heading error of 0.15°. Additionally, the vehicle’s dynamic stability is notably enhanced: the yaw rate is reduced by 9.6% and 15.7% on high- and low-adhesion roads, respectively, while the sideslip angle is decreased by 13.2% and 18.4% under the same conditions.
Yu, Hanzhengnan, Hou, Xiaoyi, Zhang, Hao, Zhou, Weichen, Liu, Yu
Real-time Vehicle Speed Detection Based on YOLOv11 and DeepSORT2026-99-15959/11/2026
The technology of real-time and effective vehicle speed detection is considered a key technology to improve traffic monitoring efficiency and traffic safety management grade. To address the limitations of traditional speed detection schemes—including reliance on dedicated hardware, poor environmental adaptability, and high construction and maintenance costs—this paper proposes a r10eal-time vehicle speed detection system based on YOLOv11 and the DeepSORT algorithm. The proposed system uses the YOLOv11 target detection algorithm as its primary model. DeepSORT multi-target tracking technology is integrated to enhance tracking performance. Speed measurement is implemented using a virtual detection line. This approach enables accurate vehicle detection, continuous tracking, and real-time speed measurement within video frames. Through the experiments, the result shows that the improved YOLOv11n model reaches mAP@0.5 of 0.982 and a recall rate of 0.956 in the test set, higher than the YOLOv8n and YOLOv5s models. The speed detection error can be restricted to 3 km/h, satisfying the real-time detection need. There is no need for road surface modification, and the detection system has a flexible layout, providing a dynamic basis for traffic law enforcement and traffic data support for road construction and traffic control optimization.
Jin, Guowei, Ma, Wenlong, Jiang, Dali, Li, Nan