Browse Topic: Human Factors and Ergonomics

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Passive Thermal Management of Battery Disconnect Units for Fast-Charging Electric Vehicles: A Comparative Study of Phase Change Material Heat Transfer Configurations2026-01-0759To be published on 07/01/2026
Reducing charging time remains a critical challenge for the widespread adoption of electric vehicles (EVs). Limited charging infrastructure availability, combined with the long duration required for battery recharging, significantly affects user acceptance. As a result, fast-charging technologies are increasingly being introduced in both newly designed EV platforms and existing vehicles through retrofitting solutions. Despite their benefits, fast-charging systems impose substantial thermal loads on vehicle components, charging stations, and associated power electronics. Excessive heat generation can compromise performance, reliability, and safety, making effective thermal management a key design concern. Within the high-voltage architecture, the Battery Disconnect Unit (BDU) plays a vital role by monitoring and controlling the connection of the battery to the powertrain and charging system. Traditionally, BDUs are designed for conventional charging power levels; however, higher
Salameh, Georges, Goumy, Guillaume, Frecinaux, Anthony, Ratajczack, Christelle, Palluel, Marlène, Noiseau, Pascal, Lardeux, Sébastien
Estimating Driver Field of View in Active Safety Systems2026-01-0775To be published on 07/01/2026
Driver Monitoring Systems (DMS) are an important component of active safety systems, continuously evaluating the driver’s state and issuing real-time warnings. As defined by the SAE Levels of Automation, driving tasks are increasingly transferred from the driver to the vehicle at Level 2, however, the driver remains fully responsible for monitoring the driving environment. Current implementations, such as Driver Drowsiness and Attention Warning (DDAW), assess driver alertness, while Advanced Driver Distraction Warning (ADDW) ensures that the driver maintains visual focus. Nevertheless, these systems do not identify the specific objects or regions the driver is observing. This limitation motivates the presented research question: can an in-car monitoring system be integrated with external environment perception sensors to infer the driver’s Field of View (FoV)? This paper presents a system consisting of a driver-facing camera and a front-view camera. Facial features, including gaze
Ji, Dejie, Lausch, Hendryk, Flormann, Maximilian, Henze, Roman
Methodological framework for the derivation of objective criteria for ride comfort assessment2026-01-0765To be published on 07/01/2026
In recent years, the automotive industry has faced increasing pressure to accelerate development cycles and reduce associated costs, while simultaneously meeting rising standards of ride comfort driven by the ongoing integration of autonomous driving functionalities. Consequently, it has become essential to ensure that ride comfort attains a high degree of maturity at the very early stages of the automotive development process. This necessitates the establishment of objective criteria that enable the reliable estimation of subjective ride comfort, utilizing simulation-based assessment methods. This study introduces a methodological framework designed to systematically translate the manufacturer specific subjective perception and assessment of ride comfort into objective descriptions using a dynamic driving simulator. The framework is conceived as a generic approach, enabling the comprehensive application to a wide spectrum of subjective ride comfort phenomena, while being specifically
Stroesser, Simon, Zwosta, Tobias, Angrick, Christian, Neubeck, Jens, Wagner, Andreas
Context-Dependent Assessment of Driving Dynamics and User Perception in Automated Driving2026-01-0757To be published on 07/01/2026
Automated driving systems are increasingly operating in complex urban environments, where driving behavior is shaped not only by technical requirements but also by how users perceive the vehicle’s motion. While many studies evaluate automated driving performance in isolated maneuvers or specific traffic situations, little empirical evidence exists on whether similar driving dynamics are perceived consistently across different urban contexts. This work investigates whether comparable motion patterns, such as acceleration profiles or steering behavior, are evaluated similarly or differently when occurring in roundabouts and intersections using data from real-world driving studies. The empirical basis consists of two user studies. In the first study, 24 participants experienced automated driving in roundabout scenarios in public traffic. In the second study, 20 participants experienced automated driving through intersections on a test track under defined boundary conditions. In both
Panzer, Anna, Strenge, Emma, Iatropoulos, Jannes, Henze, Roman
Mind the Gap: Quantifying Behavioral Fidelity in CARLA using Naturalistic Drone Data2026-01-0771To be published on 07/01/2026
The rapid advancement of autonomous driving systems, particularly SAE Levels 3 and 4, requires rigorous validation strategies to ensure safety during handover and fallback procedures. Although virtual environments provide the necessary scalability, the simulation-reality gap poses a significant risk to the reliability of human-in-the-loop (HITL) assessments. This paper presents a comprehensive, empirical investigation into the transferability of human driving behavior from the Car-Learning-to-Act (CARLA) simulation environment to real-world traffic situations. Using the exiD dataset, which comprises high-precision, drone-recorded, naturalistic trajectories from German highways, we systematically reconstructed distinct traffic scenarios. These scenarios included lane changes, cut-in maneuvers, and curve navigation. Twenty-five participants navigated these scenarios in a driving simulator. The study employed a robust, multidimensional analytical framework to compare the simulated
Rebling, Patrick, Alphan, Metehan, Nenninger, Philipp
UMV Peoplemover: Towards a modular fully automated vehicle research platform2026-01-0784To be published on 07/01/2026
The UMV Peoplemover 2+2 is part of a modular vehicle family (Urban Modular Vehicle) that includes derivatives for passenger and cargo transport in urban environments. The platform supports automated movers as well as conventionally controlled vehicles with a human driver, ensuring high flexibility across applications. The modular platform enables the extensive use of common parts, allowing the efficient and cost-effective realization of multiple vehicle variants. The increased share of common parts also improves sustainability by reducing derivative-specific parts, material usage, and production complexity. A drivable demonstrator of the UMV Peoplemover 2+2 has already been realized. The vehicle is designed for the automated transport of up to four occupants in a 2+2 vis-à-vis seating arrangement and is targeted at demand-oriented shuttle services. While the drivable demonstrator validated the proof of concept, it lacked the core Level 4 hardware and software stack for automated
Pohl, Eric, Schmid, Fabian, Münster, Marco, Siefkes, Tjark, Stuebler, Tillmann, Mohammed, Shawan
Towards a Smarter E-Bike: Enhancing Energy Efficiency through Adaptive Speed Control2026-01-0736To be published on 07/01/2026
This paper presents the development of a speed controller for e-bikes, designed as part of an energy-adaptive assistance system. The controller provides riders with appropriate support along planned routes, based on the available battery capacity. The control concept is intended for integration into existing commercial e-bikes without requiring extensive modifications to the drive system. Therefore, the rider remains part of the control loop, adjusting the support mode according to instructions from the controller. The speed controller is implemented as a rule-based state machine, enabling comprehensible design and parameterization Since the rider must manually switch between support modes while riding, the control logic incorporates hysteresis and dead times to ensure stability, prevent oscillations and avoid frequent mode switching. The user interface is a smartphone application that issues visual and audio instructions for switching support modes. An initial, system-independent
Rauch, Yannick, Simmann, Gabriel, Schneider, Manuel, Goss, Christian, Kriesten, Reiner
Spatial Noise Acquisition at the Driver's Position in an Electric Vehicle with Increased Accuracy2026-01-0723To be published on 06/20/2026
In vehicles with electrified powertrains, high-frequency tonal noise components have become increasingly prominent and can be perceived as particularly annoying by the driver. While recent advancements in international standardization—such as ECMA-74 and ECMA-418—have led to powerful new algorithms for tonal noise visualization and analysis, like our Tonality-Heatmaps, the measurement side still lacks sensor setups that adequately reflect the spatial sensitivity of noise, especially for tonal components. This challenge is amplified in enclosed vehicle cabins, where room modes create local minima and maxima that become increasingly dense at higher frequencies. As a result, even small head movements can lead to noticeable differences in perceived tonal noise. Current measurement approaches do not sufficiently account for this spatial variability. This contribution addresses the absence of tailored solutions for the driver’s position by introducing an improved microphone arrangement that
Schecker, Daniel, Rittenschober, Thomas
Field-Based Evaluation of Physiological Fatigue Reduction in Fuel Cell Refuse Collection Vehicle Using Heart Rate Variability2026-01-0690To be published on 06/20/2026
This study compared the physiological fatigue of drivers and accompanying workers operating diesel-powered (DI) and fuel cell-powered (FC) garbage compactor trucks under real-world working conditions. Reducing driver fatigue is critical for ensuring occupational safety and maintaining work efficiency, as fatigue in waste collection tasks is influenced by multiple factors such as vibration, noise, and vehicle operation characteristics. In this study, heart rate sensors and smartwatches were used to continuously monitor physiological responses during identical driving routes. Fatigue was evaluated using heart rate variability (HRV) indices—specifically, the root mean square of successive differences (RMSSD) and Lorenz plot (LP) area—calculated from RRI data. The results indicated that the RMSSD of drivers in FC trucks was approximately 60% higher and their LP area about 50% larger than those in diesel trucks. For accompanying workers, RMSSD was around 20% higher and LP area approximately
Utsumi, Atsuko, Yakoh, Takahiro
Experimental Validation of Frame-Dependent Gyroscopic Frequency Splitting in a Freely Rotating Tire Using Wireless MEMS Accelerometers and Scanning Laser Doppler Vibrometer2026-01-0700To be published on 06/20/2026
Gyroscopic effects split circumferential traveling-wave resonances of rotating structures into forward and backward branches. This work first analyzes the splitting in the co-rotating (Lagrangian) frame to provide physical intuition for the evolution of the two branches with spin speed. A transformation to the inertial (Eulerian) frame is then derived, showing that the observed frequencies are shifted by a kinematic Doppler-like term that acts with opposite sign on the forward and backward waves, leading to different Campbell-diagram slopes depending on the observation frame. The resulting framework is validated experimentally on a freely rotating, unloaded tire using two complementary sensing modalities: wireless on-tire accelerometers (co-rotating view) and a scanning laser Doppler vibrometer (inertial view). A frequency-domain SVD-based identification (FDD/ODS-SVD) is used to extract poles and deformation patterns over a range of spin speeds, enabling Campbell diagrams in both
del Fresno Zarza, Javier, Naets, Frank
Vibro-Acoustic simulation for vehicle audio design2026-01-0670To be published on 06/20/2026
Acoustic user interfaces and audio experiences are among the leading comfort factors in new vehicle interior designs. OEMs are more and more focusing on loudspeaker design and positioning, to provide the most immersive experience to the customers. The industrial target is to be able to predict the performance of an audio system in early design phases. This paper presents a methodology to model source-receiver transfer functions in a full-scale vehicle cabin and investigates the installation effect of the speakers in a real car door. A hybrid methodology is developed to be able to model the loudspeaker in different environment.
Zerrad, Mehdi, Errico, Fabrizio, Mordillat, Philippe
Development of a Convolutional Autoencoder-Based Unsupervised Classification and Visualization Model for Extracting Feature Frequency in C-EPS Fault Diagnosis2026-01-0717To be published on 06/20/2026
In the automotive industry, deep learning models such as convolutional neural networks, autoencoders, and transformers have been actively studied to improve defect detection rates in End-of-Line (EOL) processes. However, applying these approaches to the field of Noise, Vibration, and Harshness (NVH) faces several practical challenges. ① Difficulty in securing sufficient training data and risk of overfitting due to longer evaluation times compared to other data types. ② Label imbalance caused by the relatively small amount of defective data. ③ Reduced labeling accuracy due to human error. ④ Decreased model robustness under domain shifts such as jig variations, evaluation environments, signal-to-noise ratio (SNR), and the occurrence of new abnormal noises. ⑤ Constraints in application due to compatibility issues with existing evaluation equipment. To address these issues, this study proposes an unsupervised learning-based method for classifying operating noise data of Column-type
Park, Jun-Seo, Jo, Hyeon-Choel, Cho, In-Je, Seo, Jae-Yong, Yoo, Seong-Sik
Automating DO-178C Verification and Security Compliance in DevSecOps CI/CD Pipelines for Safety Critical Avionics Software2026-26-0717To be published on 06/01/2026
This paper presents an automated framework for security compliance and quality assurance in DevSecOps CI/CD pipelines, specifically designed for safety-critical avionics software. The framework integrates regulatory compliance checks, security validation, and robust verification directly into the software development lifecycle, supporting continuous integration and delivery for aerospace applications. Automated processes such as code compilation, coding standards compliance, Cyclomatic Complexity Measurement, Sources Line of Code and CRC validation on target hardware are seamlessly orchestrated to maintain consistency and reliability. The system generates comprehensive compliance reports, highlights coding standard violations and security issues, and notifies relevant stakeholders to facilitate timely resolution and corrective actions. As new code is checked in, the framework automatically initiates all verification and compliance tasks, ensuring that every software update is
Bhagwat, Shashank Ravi, Changappa, Naveen Kumar, Nath, Sunny
Mitigating Cracking in COP Optics through Annealing and Step-Torquing2026-26-0764To be published on 06/01/2026
Polymeric optical materials such as Cyclo Olefin Polymer (COP) are adopted in aerospace lighting systems due to their excellent optical clarity, dimensional stability, moldability and weight saving advantages over glass. However, their relatively low toughness and the presence of residual molding stress make them prone to crack initiation during mechanical fastening. During its installation, crack formation was consistently observed around self-tapping screw interfaces, raising concerns over reliability, maintainability, and compliance with durability requirements. A structured Design of Experiments (DOE) was performed to identify root causes and evaluate potential mitigation methods. The investigation revealed that residual stresses in the COP material, combined with localized stress concentrations during screw tightening, were the primary drivers of crack initiation. Two complementary process improvements were identified and validated as part of mitigation plan: (i) annealing of the
S, Nikhil, Singh, Abhimanyu Kumar, Katageri, Praveen, SP, Pradeep, Chandra, Praveen
Non-Intrusive Fatigue Detection for Pilots2026-26-0793To be published on 06/01/2026
Pilot fatigue represents a critical concern in aviation safety, as it can significantly impair cognitive functions, decision-making abilities, and reaction times. In addition to decreasing performance, in-flight chronic fatigue has negative long-term health effects. Possible causes of fatigue include sleep loss, extended time awake, circadian phase irregularities and workload. Conventionally, the risk due to fatigue in aerospace is reduced by flight time limits and controlled rest requirements. Despite regulations limiting flight time and enabling optimal rostering, fatigue cannot be prevented completely. Hence, there is need to detect pilot fatigue in real time. There is ongoing research to detect pilot fatigue using devices that can capture Electroencephalogram (EEG) and Electrocardiogram (ECG). Though these devices have high fidelity, they are intrusive and can limit pilot activity. This limitation could potentially be overcome by non-intrusive devices such as a smart watch/wrist
Nyamagoudar, Vinayak, P R, Namratha, Ramachandran, Venkataramani
Integrating Human factors and Predictive Modeling for Enhanced Aviation Safety: A Data - Driven Approach to Risk Mitigation and System Design2026-26-0795To be published on 06/01/2026
This study presents a data-driven approach for strengthening aviation safety by integrating human factors assessment with modern predictive modeling techniques. The work focuses on understanding how human performance, operational conditions, and system-level interactions collectively influence safety risk, and how these interactions can be quantified to support improved design and decision-making. Unlike previous studies that address human factors or predictive modeling in isolation, this research offers a unified framework that links causal human factors indicators with statistical modeling, feature extraction, and machine learning based risk estimation. The novelty of this work lies in the structured pipeline that transforms raw categorical and narrative human factors information into measurable predictors that can be analyzed using structural modeling and machine learning. The methodology includes data preparation, dimensionality reduction, latent pattern discovery, dependence
Valiyaparambil, Praveen
AI-Led Sustainability Strategy: Driving Product Value from Birth to Disposal2026-26-0781To be published on 06/01/2026
Aerospace products operate within highly complex, safety-critical environments and endure extended lifecycles, often spanning decades. Sustaining their operational value requires rigorous management of Safety, Reliability, and Availability (SRA), while global Environmental, Social, and Governance (ESG) mandates demand parallel progress toward sustainability goals. This paper introduces an AI-driven strategy that integrates these dual imperatives—Sustenance Management and Sustainability Management—within a unified Product Lifecycle (PLC) framework. The proposed approach leverages Artificial Intelligence across five PLC phases: Generative Design, Detailed Design & Verification, Manufacturing & Industrialization, Operations & Maintenance, and End-of-Life Circularity. Anchored by a certified Digital Thread, this framework ensures seamless, auditable data flow from concept to disposal. Using Life-Limiting Parts (LLPs)—such as high-stress turbine discs—as a case study, the paper demonstrates
Srinivasan, Karthik, G.V.V., Ravi Kumar, Vaderahobli, Devaraja Holla, Bhate, Ujwal, Veluri, Sastry
Autonomous Aircraft Docking: A Vision-Based Approach to Aircraft Parking Systems2026-26-0786To be published on 06/01/2026
Automated aircraft parking systems enhance airport ground operations by enabling precise and autonomous docking of aircraft at gates. These systems reduce turnaround time, minimize human error, and optimize apron space through real-time object detection, obstacle avoidance, and dynamic path planning. Unlike fixed guided-path methods, the proposed system adapts to congestion and environmental conditions such as low visibility, ensuring safety and efficient maneuvering. Validation through simulation demonstrates the system’s potential to improve operational resilience and support scalable automation in future airport infrastructure.
Penugonda, Navya Sunaina, Ediga, Venkatadiwakar Goud
Augmented Reality and Multimodal Interfaces for Astronaut Training and In-Orbit Operations2026-26-0796To be published on 06/01/2026
Augmented Reality (AR) and multimodal human–machine interfaces (MMI)— combining visual overlays, voice, gesture, eye- tracking, and biometric sensing—are maturing into flight-relevant technologies capable of transforming astronaut training and in-orbit operations. These interfaces can reduce task time, lower procedural errors, and mitigate cognitive workload, thereby strengthening crew autonomy and mission safety. Global operational experiences from International Space Station (ISS) augmented- reality trials and related international programs are synthesized to inform the proposed system architecture and validation framework: (i) an overview of India’s current AR/MMI-related ecosystem relevant to human spaceflight, including astronaut training pipelines and research collaborations; (ii) a mission-grade AR/MMI system architecture and multimodal fusion/decision logic suitable for human-rated operations; (iii) algorithms and programming examples for AR-driven finite-state-machine (FSM
Yadav, Anoop Singh
Adaptive HVAC Strategies for Enhanced Cabin Thermal Comfort, Air Quality and Energy Efficiency2026-26-0791To be published on 06/01/2026
Passenger comfort within vehicles and aerospace cabins relies on finely tuned management of temperature, air quality, and energy use. This paper proposes an integrated HVAC framework that combines zonal climate control, intelligent airflow distribution, and real-time sensor data to maintain thermal balance across different cabin zones. Leveraging predictive thermal load modelling and machine learning, the system anticipates environmental changes—such as sudden shifts in external temperature or passenger load—and proactively adjusts heating and cooling outputs. Simultaneously, air quality is enhanced through a multistage filtration system, active air purification technologies, and dynamic CO₂ concentration monitoring. Comfort assessment integrates PMV (Predicted Mean Vote) and PPD (Predicted Percentage Dissatisfied) indices to adapting environmental conditions. Simulations and early-stage prototypes improve energy savings and improve occupant comfort and air quality. The proposed HVAC
Mudavath, Lehitha Sai, Patil, Ashish, Saha, Sudipta
Zero Waste Manufacturing in Aerospace: Circular Design Approaches from Concept to End-of-Life2026-26-0775To be published on 06/01/2026
Achieving zero-waste manufacturing in aerospace requires a shift from end-of-pipe waste mitigation toward circular design principles embedded early in product development. This paper presents a practical framework for integrating circularity into aerospace systems through five design pillars: design for modularity and disassembly, material substitution to enhance recyclability, waste segregation and characterization, component-level circularity readiness scoring, and collaborative supplier engagement. To operationalize this approach, a Circularity Readiness Assessment Tool (CRAT) is developed to evaluate design alternatives against criteria such as disassembly ease, material recyclability, manufacturing waste potential, end-of-life recovery pathways, and supplier take-back mechanisms. The framework supports multi-criteria decision-making by complementing traditional aerospace design drivers including weight, performance, cost, and safety. The methodology is demonstrated through a case
S, Chaitra
A GenAI-Based Approach for Real-Time Multilingual In-Flight Communication Systems2026-26-0784To be published on 06/01/2026
In today’s global aviation industry, passenger experience is strongly influenced by effective communication. In-flight announcements, often limited to English and a single local language, can create confusion and stress for international travelers who may not be fluent in either. This communication gap not only impacts passenger comfort but also poses potential risks in conveying time-sensitive or safety-critical information. Recent advances in Generative Artificial Intelligence (GenAI), particularly in speech recognition, neural machine translation, and naturalistic text-to-speech, provide a pathway to overcome these challenges. This paper explores the concept of real-time multilingual in-flight announcements delivered in each passenger’s preferred language through connected headphones or personal devices. The proposed system architecture integrates speech-to-text conversion, language translation, and speech synthesis with aircraft infotainment platforms. Potential applications range
Mishra, Ashwini, Kature, Kartik, Patil, Ashish
PMHS Sled Testing of Reclined Small Female Occupants: Pelvic Dynamics and Injury Evaluation2026-22-00015/28/2026
As automated vehicle technologies enable increased seat recline angles during travel, understanding the biomechanics of injury under these novel occupant postures becomes imperative. This study evaluated the pelvis injury response and associated kinematics of reclined small female post-mortem human surrogates (PMHS) subjected to frontal sled tests across three restraint configurations. Each configuration varied in seat stiffness and the presence of a knee bolster to assess their influence on pelvic dynamics and submarining risk. Nine PMHS tests were conducted using a consistent reclined posture (38° thorax, 75–80° pelvis angle) and production restraint systems. Submarining probability was estimated using a validated logistic regression referenced from previous study. Distinct pelvic kinematics, fracture patterns, and associated injury mechanisms emerged across the test configurations in the current dataset. Configuration 1, featuring a stiffer seat without a knee bolster, exhibited
Somasundaram, Karthik, Driesslein, Klaus, Pintar, Frank A.
SAE TOMORROW TODAY - The Brain Behind AI-Powered Vehicles135695/27/2026
What if the brain of your car wasn't just smart but continuously learning, scaling, and orchestrating everything from safety to autonomy in real time? Listen in as we sit down with Anshuman Saxena, Vice President and General Manager of ADAS & Robotics at Qualcomm Technologies, Inc., to explore how the Snapdragon Ride Pilot is reshaping the path to automated driving. From the rise of physical AI to systems that unify sensors, software, and real-time decision-making, we break down what it actually takes to move from fragmented ADAS features to a fully integrated, AI-refined vehicle. If you want to understand where autonomy is really headed (and what the industry might still be underestimating), this is a conversation you won't want to miss. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility
Patterson, Lori
Toward Human-Centric Autonomous Vehicle Control: A Systematic Model-Based Approach to Motion Sickness Mitigation and Path Tracking10-10-03-00235/22/2026
Autonomous Vehicles (AVs) offer unprecedented opportunities to design control strategies that could be able to simultaneously enhance safety, performance, user experience, time efficiency, and the environmental impact of mobility. However, as automation levels increase, a paradigm shift becomes not only necessary but imperative: the integration of human needs into mobility objectives. This includes not only traditional comfort considerations but also minimizing Motion Sickness (MS), a largely under-explored challenge in control strategy design. In recent literature, several methodologies for modeling and mitigating MS have been proposed, yet their integration into vehicle control logics remains limited, often restricted to isolated and specific case studies, with the research area largely unexplored, particularly with respect to the generalization of the proposed methods. This work introduces a theoretically grounded multi-objective Nonlinear Model Predictive Control (NMPC) framework
Ponticelli, Lorenzo, Bottiglione, Francesco, Rini, Gabriele, Timpone, Francesco, Sakhnevych, Aleksandr
Energy Saving and Personalized Thermal Comfort Control Based on Reinforcement Learning and Decision Tree2026-99-17145/22/2026
Indoor thermal comfort is closely related to people’s health and work efficiency. Control systems typically consume a large amount of energy to maintain a comfortable thermal environment. Currently, reinforcement learning is widely applied to optimize thermal comfort control systems. However, existing research mainly adopts universal thermal comfort evaluation models that aim to satisfy the majority of people, which makes it difficult to quickly and accurately reflect the specific thermal comfort needs of individuals. As a result, the hot environment is neither comfortable nor energy-efficient in practical use. Therefore, this paper proposes an energy-saving personalized thermal comfort control method based on decision trees and reinforcement learning. First, decision tree learning is used to obtain an individual thermal comfort evaluation model from a small amount of historical data. Then, this individual comfort model is combined with energy consumption to form a reward function
Li, Xianying
Design and Research of an Elderly Mobility Assist System Based on Intelligent Power-Assistance Device2026-99-07375/15/2026
The aging of the population has been a key issue worldwide, with mobility and fall of the elderly an important problem to be solved. In this paper, we propose an elderly mobility assist system based on the intelligent power-assisted device consisting of an assistive cane and an intelligent companion. It has the functions of standing support after falling, daily support and on-site rest. The assistive cane adopts a two-stage expansion mechanism of crank and slider structure, which forms a stable triangular support after unfolding, so that the patient can stand safely. The intelligent companion platform is driven by drive wheels, equipped with pushrod motors and vacuum suction devices, it can automatically approach the user and form an stable support column when the cane is in the out-of reach range; the control system is designed by combining microcontroller, camera object recognition, wristband remote control, to realize automatic steering and autonomous navigation at differential
Yu, Chenxi, Wang, Longyi, Zhu, Huayun, Dong, Yan, Mi, Ruixue, Zhu, Lihong
Multi-Mode Control Strategy for Controllable Vehicle Suspension Systems2026-99-07125/15/2026
2−3
Li, Zhiying, Li, Jei, Zhu, Anding, Bai, Xianxu, Li, Weihan, Li, Rui
Standard Practice for Force Protection and SurvivabilitySAE1008A (Current)5/15/2026
According to SAE6906, Force Protection and Survivability (FPS) is the Human Systems Integration (HSI) domain that facilitates system operation and personnel safety during and after exposure to hostile situations or environments. Force protection refers to all preventive measures taken to mitigate hostile actions against Department of Defense (DoD) and Department of Homeland Security (DHS) (e.g., U.S. Coast Guard, Customs and Border Patrol, Immigration and Customs Enforcement, etc.) personnel. Survivability denotes the capability of the system and/or personnel manning the system to avoid or withstand man-made hostile environments without suffering an abortive impairment of his/her ability to accomplish its designated mission. Damage due to enemy or fratricidal action, or even equipment failure, will endanger the warfighters' well-being and place them into a life-threatening situation.
G-45 Human Systems Integration
Driving Behavior Heterogeneity Identification with Action Patterns Relationship2026-99-07525/15/2026
Identifying driving heterogeneity is critical for enhancing the strategy learning capabilities of autonomous driving systems, as well as improving their safety and efficiency. This research proposes a novel driving heterogeneity identification framework. The framework consists of three core processes: action phase extraction, action relationship modeling, and behavior heterogeneity identification. First, a rule-based segmentation method is employed to systematically decode and interpret the inherent variations in human driving behavior. Subsequently, an action relationship modeling method is introduced to characterize the temporal relations between the acquired action phases. Finally, to mitigate the inaccurate identification caused by the sparse distribution of critical driving events in long-sequence data, a semantic encoding method is applied to remap the driving behavior space. Experimental results on the Lyft level-5 dataset validate the effectiveness of the proposed framework
Yin, Hui, Zhang, Qinyao, Li, Xiaojian, Mo, Hangjie
Design of a Modular High-Power High-Repetition-Rate Semiconductor Pulsed Laser Power Supply2026-99-07165/15/2026
μsμs
Huang, De, Lu, Jiawei, Yang, Zhiqing, Xv, Ziyi, Xing, Hui
Permanent or Fixed Place Flight Deck Head-Up DisplaysARP4102/8B (Current)5/14/2026
This SAE Aerospace Recommended Practice (ARP) provides criteria for the design, installation, operation, and training aspects of head-up display (HUD) systems in transport category aircraft, with emphasis on pilot interface and operational requirements. The recommendations apply to permanently installed (including stowable) HUDs that display primary flight information, including those integrating enhanced flight vision system (EFVS) imagery. The intent is to ensure HUDs are designed and used in a manner that improves pilot situational awareness and flight technical performance across all phases of flight, up to and including low-visibility operations. While technical design standards (optical performance, hardware specs, etc.) are defined in documents like ARP5288 and AS8055, this document focuses on pilot usage considerations and human factors. HUD systems addressed here are typically designed to support a fail-passive operational concept applicable to Category III instrument approach
S-7 Flight Deck Handling Qualities Stds for Trans Aircraft
Letter from the Editor-in-Chief09-14-01-00015/13/2026
Letter from the Editor-in-Chief
Hardy, Warren N.
Letter from the Guest Editor09-14-01-00345/13/2026
Letter from the Guest Editor
Tylko, Suzanne
SAE TOMORROW TODAY - Why Curing Motion Sickness Is Key to AV Success135675/11/2026
Did you know that motion sickness affects 1 in 3 people? As AVs gain traction and drivers become passengers, it may be the biggest barrier to the future of autonomous mobility. With a focus on addressing the root cause of motion sickness, Motion Sync offers breakthrough solution: a haptic pre-activation system that helps passengers anticipate vehicle movement with a personalized in-cabin experience that could redefine comfort and productivity. Listen in as we sit down with Dr. Daniel Sousa Schulman, CEO and Founder of Motion Sync, to unpack the science behind motion sickness and why it's a critical issue for EVs, robotaxis, and self-driving cars. You'll learn why passengers get sick, why drivers don't, and how EVs can actually make symptoms worse. As a topic critical to the success of autonomous vehicles, it's a conversation you don't want to miss. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take
Patterson, Lori
Rear-Impact Crash Injury Patterns and Predictors: Insights from Contemporary CISS and CIREN Field Data09-14-01-00295/4/2026
The objective of this study was to investigate occupant injury patterns and predictors in rear-impact crashes using recent US field data. Cases were queried from the Crash Investigation Sampling System (CISS, 2017–2023) and the Crash Injury Research and Engineering Network (CIREN, 2017–2024), yielding 1923 front-row outboard occupants from 1533 crashes. Crash documentation and vehicle photographs were manually reviewed to classify seatback deformation magnitude and secondary impact severity. Multivariable logistic regression models estimated associations between occupant, vehicle, and crash characteristics and Abbreviated Injury Scale (AIS) ≥ 2 and AIS ≥ 3 injury outcomes across body regions. Sensitivity analyses included CISS-only, weighted, single-event, and interaction models. Thoracic injuries were further subdivided into skeletal and cardiopulmonary categories. Findings reflect associations within the pooled CISS + CIREN analytic sample rather than nationally representative injury
Lockerby, Jack, Rudd, Rodney
Driver Understanding of Yellow Indication Laws and Preferences for Configuration of In-Vehicle Alerts for Dilemma Zones09-14-01-00065/4/2026
Drivers frequently encounter Type II dilemma zones at signalized intersections, where the decision to stop or proceed during the onset of a yellow indication can be ambiguous. Decision-making relies on drivers’ expectations of the yellow change interval duration and behavioral factors. While boundaries of these zones are well studied, less is known about how familiar drivers are with their local yellow indication laws, which vary from state to state, and whether their typical reactions to yellow indications align with the laws. Existing interventions like signal timing adjustments, improved vehicle detection, and advance warning signs reduce the number of drivers caught in dilemma zones but may not reach distracted drivers. In-vehicle alerts tailored to dilemma zone scenarios are a potential solution not yet implemented widely in North America. This study addresses how drivers may interpret these alerts. A web-based survey of 640 licensed drivers in Michigan and Washington (ages 18–85
Anderson, Erika, Jashami, Hisham, Ahmed, Ananna, Hurwitz, David
The Effect of Initial Foot Position on THOR-50M and THOR-05F Lower Leg Response in a Realistic Vehicle Buck09-14-01-00085/4/2026
This study aims to explore and evaluate the effect of various foot positions on the kinematic and kinetic response of the lower extremity during frontal crashes using a realistic vehicle interior. Frontal impact sled tests were performed with the Test Device for Human Occupant Restraint, 50th-percentile Male (THOR-50M) and Test Device for Human Occupant Restraint, 5th-percentile Female (THOR-05F) anthropometric test device (ATD) in the driver’s seat of a midsize SUV testing buck (with realistic interior components including an instrument panel with steering wheel and steering wheel airbag, seat, three-point seat belt with pretensioner and force-limiter, accelerator pedal, brake pedal, knee airbag, and seat belt retractor pretensioner). Six sled tests were performed in two principal directions of force (PDOF) [three each in frontal (0°) and oblique (−20°) configurations]. The right foot was positioned on the accelerator pedal, fully on the brake, and half on the brake. A single test was
Noss, Junior, Donlon, John-Paul, Morris, Anna, Samier, Germain, Park, Joseph, Forman, Jason
Modification and Validation of a Finite Element Model of a Pedestrian Dummy09-14-01-00125/4/2026
Aims of the research This study aims to modify the lower body (the pelvis, thigh, and leg) of the mid-sized male pedestrian dummy FE model by considering the latest version of the physical dummy and to evaluate both the accuracy by comparing test results of the past studies and the biofidelity specified in SAE J2782 in both component and full-scale validations. Methods 1 Component validation The validation of the modified pelvis model was performed in dynamic lateral compression simulations. The sacrum and the pubis force-deflection responses of the iliac or the acetabulum impact were measured. The modified thigh and leg models were evaluated in a dynamic 3-point lateral bending simulation, measuring the force-deflection responses. The results from the simulations were compared with test results and the biofidelity requirements. 2 Full-scale validation The whole-body model was updated by incorporating these modified component models. The model of the generic buck developed for the
Asanuma, Hiroyuki, Gunji, Yasuaki, Mori, Fumie, Nagashima, Akiko
Interactions of Rear-Facing Child Restraints in Frontal Crash Tests09-14-01-00105/4/2026
The aims of this study were to investigate the kinematics of child anthropomorphic test devices in a large sample of rear-facing child restraint system installations and the effects of anti-rebound features and load legs on the kinematics of rear-facing child anthropomorphic test devices. The test matrix included a general sample of 70 rear-facing child restraint system installations to observe trends in frontal crash tests; 14 full-scale crash tests with paired comparisons to investigate the effect of anti-rebound features; and five paired comparisons of rear-facing child restraint systems installed with and without a load leg. The paired t-test was used to determine the statistical significance of differences in kinematic responses. In the general sample, 84% of anthropomorphic test devices in infant seats with the base in outboard seats interacted with the first-row seat. In 52% of tests, the anthropomorphic test device head directly contacted the front seatback. Head accelerations
Tylko, Suzanne, Tang, Kathy
Characterization of Front Row Occupants Involved in Motor Vehicle Crashes Compared to ATDs and the U.S. Population09-14-01-00275/4/2026
Currently, adult anthropomorphic test devices used in regulatory and consumer information crash testing in the United States are targeted to represent a small female (5th percentile) and an average male (50th percentile). The anthropometry determined previously might not represent the current population, or as investigated in the current study, those that are at least moderately injured during a motor vehicle crash. The objective of this study was to use field data to determine if the current frontal anthropomorphic test devices are representative. Data from the National Automotive Sampling System–Crashworthiness Data System (2010-2015) and Crash Investigation Sampling System (2017–2023) were queried for sex, age, size, and injury information for front seat occupants in frontal crashes. Additional datasets used were from the National Trauma Data Bank and the Centers for Disease Control and Prevention. According to field data, the most frequently injured female and male is approximately
McNeil, Elizabeth, Atwood, Jonathan, Rudd, Rodney, Craig, Matthew
Visual–Language Model–Driven Annotation and Analysis of Maneuver Data for Enhanced Vehicle Safety09-14-01-00325/4/2026
Vehicle maneuver data are essential for perception and planning in advanced driver-assistance systems (ADAS) and automated driving systems (ADS). While high-quality annotations improve machine-learning performance, existing maneuver datasets remain fragmented, labor-intensive to annotate, and inconsistent in semantic richness. Challenges persist in scalability, interpretability, and contextual labeling. This article establishes a structured framework for maneuver data analysis by combining a systematic review of existing resources with the development of a new multimodal dataset. First, we conduct a systematic review of publicly available datasets such as HDD, KITTI, BDD-X, D2CAV, Brain4Cars, DrivingDojo, and the Driving Behavior Database. We further evaluate the data modality and sensor configurations including event data recorders, onboard logging systems, and smartphone sensing. We then propose the Matt3r Data Collection System with modern metadata management, which integrates video
Bai, Ling, Yuan, Chongyu, Osman, Islam, Lin, Zirui, Mirab, Ghazal, Saheb, Amir, Parnian, Neda, Shapiro, Evgeny, Shehata, Mohamed S., Liu, Zheng
Geometric Variabilities and Their Effects on Impact Responses in Midsize Male and Female Occupants09-14-01-00255/4/2026
The objective of this study is to use parametric human body models (HBMs) to understand how geometric variability among individuals who have the same sex, stature, and body weight may affect the impact responses and injury outcomes, using midsize male and midsize female populations as representative cases. Methods were developed to quantify skeletal and external body surface variations using principal component analysis, regression, and residual error analysis. Based on this analysis, nine midsize male and nine midsize female geometric models were created, focusing on ribcage and pelvis variations, which account for most of the observed variability. These geometries were then applied to morph the simplified Global Human Body Model Consortium (GHBMC) midsize male model, producing 18 distinct HBMs. Each morphed HBM was subjected to nine impact scenarios, resulting in a total of 162 simulations to assess the effects of geometric variability. Substantial geometric variation was observed in
Hu, Jingwen, Lin, Yang-Shen, Boyle, Kyle, Khandare, Sujata, Bonifas, Anne, Reed, Matthew P., Hasija, Vikas
Effects of Vehicle Speed, Category, and Front-End Design on Full-Body Injury Risks of a Midsized Male Pedestrian09-14-01-00175/4/2026
This study investigated how vehicle front-end geometry, impact speed, and vehicle category influence injury risk to a midsize male pedestrian. Eighty-one generic vehicle (GV) models representing sedans, sport utility vehicles (SUVs), pickup trucks, and minivans sold in the United States were developed by morphing three base models using an automated pipeline. Front-end parameters that were varied included ground clearance (GC), bumper height (BH), hood leading-edge (HLE) height, hood length (HL), bumper lead angle (BLA), hood angle (HA), and windshield angle (WSA). Each vehicle impacted the Global Human Body Models Consortium 50th percentile male simplified pedestrian (GHBMC M50-PS) model at 30, 40, and 50 kph, totaling 243 simulations. Boundary conditions followed the European New Car Assessment Program (Euro NCAP) pedestrian test protocol. Thirty-five injury metrics were extracted across the head, neck, thorax, abdomen, pelvis, and lower extremities. Linear mixed-effects regression
Poveda, Luis, Miller, Logan E., Edwards, Colin C., Pollock, Madeline, Armstrong, William M., Hsu, Fang-Chi, Gayzik, Scott F., Weaver, Ashley A., Stitzel, Joel D., Devane, Karan S.
Injury and Kinematics of Obese PMHS in Frontal Impacts with Reclined Seating09-14-01-00035/4/2026
Objective: This study investigated injury outcomes and body kinematics in obese occupants exposed to frontal impacts while seated in reclined postures. With increasing interest in non-traditional seating configurations and a growing population of obese vehicle occupants, the objective was to evaluate how seat stiffness and restraint features influence injury patterns and whole-body excursions. Methods: Nine obese post-mortem human surrogates (PMHS; mean age: 64 years, stature: 1.70 m, body mass: 102 kg, BMI: 35 kg/m2) were tested under frontal impact conditions simulating a delta-V of 50 kph. All specimens were seated on a spring-controlled seat with a 45° reclined seatback and restrained by a three-point belt system with pretensioner and load limiter. Three configurations were evaluated: (1) stiffer seat, (2) softer seat, and (3) stiffer seat with a knee bolster 100 mm from the knees. Each subject underwent one test. Whole-body kinematics were captured using a VICON motion analysis
Somasundaram, Karthik, Yoganandan, Narayan, Pintar, Frank
Advanced Tool for Traffic Crash Analysis: An AI-Driven Multi-Agent Approach to Pre-Crash Reconstruction09-14-01-00335/4/2026
Traffic collision reconstruction traditionally relies on human expertise and, when performed properly, can be incredibly accurate. However, attempting to perform pre-crash reconstruction, i.e., reconstructing the driver and vehicle behaviors that preceded the actual crash, poses significantly more challenges. This study develops a multi-agent artificial intelligence (AI) framework that reconstructs pre-crash scenarios and infers vehicle behaviors from fragmented collision data. We present a two-phase collaborative framework combining reconstruction and reasoning phases. The system processes 277 rear-end lead vehicle deceleration (LVD) collisions from the Crash Investigation Sampling System (CISS; 2017–2022), integrating textual crash reports, structured tabular data, and visual scene diagrams. Phase I generates natural language crash reconstructions from multimodal inputs. Phase II performs in-depth crash reasoning by combining these reconstructions with the temporal event data
Xu, Gerui, Chen, Boyou, Guo, Huizhong, LeBlanc, Dave, Kusari, Arpan, Yarbasi, Efe, Ahmed, Ananna, Sun, Zhaonan, Bao, Shan
Characterization of Pedestrian Automatic Emergency Braking Acceleration in Modern Light Vehicles: Potential Implications for Occupant Safety09-14-01-00075/4/2026
The objective of this study was to characterize and compare pedestrian automatic emergency braking (PAEB) pulses in modern light vehicles to understand the loading environment that vehicle occupants are being exposed to during PAEB maneuvers. PAEB tests (n = 8008) conducted using 2018–2023 vehicle model years were analyzed. Pulse, vehicle, and impact characteristics (e.g., jerk, peak acceleration, pedestrian scenario, etc.) were derived from each PAEB test. Two k-means clustering analyses were used to group PAEB pulses with and without target collisions based on their similarity between characteristics. One-way ANOVA and Kruskal–Wallis tests were performed on the PAEB pulse characteristics to examine differences between clusters (p < 0.05). Two non-collision clusters (NC1 and NC2) were identified for PAEB pulses without collisions: NC1 had a statistically significant lower jerk (0.8 ± 0.4 g/s) and peak acceleration (1.0 ± 0.1 g) compared to NC2 (1.6 ± 0.8 g/s and 0.9 ± 0.1 g
Witmer, Maitland, Kidd, David, Graci, Valentina
An Investigation of Drowsy Lane Departures from Driving Simulator Studies09-14-01-00145/4/2026
NHTSA is conducting research to evaluate the current state-of-the-art technology for lane departure warning (LDW) and lane-keeping assistance (LKA) technology. NHTSA is undertaking research to understand the nature of real-world lane departures and recovery behaviors. While some information about lane departures can be learned from crash datasets, the purpose of this work was to mine simulator datasets for lane departures, analyze them in greater detail than is possible from crash reports or naturalistic studies, and link their characteristics to driver drowsiness. The objective of the study was to determine whether there are differences in lane departure characteristics as a function of driver drowsiness. This research used a novel approach by combining data from six different driving simulator studies on driver drowsiness. The dataset included a sample of 380 drivers. Study drives occurred during overnight hours after periods of sleep deprivation, with participants being awake for at
Schwarz, Chris, Gaspar, John, Shull, Emily, Venegas, Michael
Comparative Analysis of Thoracic Injury and Causative Factors across Sexes in Serious Frontal Motor Vehicle Collisions in the Crash Injury Research and Engineering Network Database09-14-01-00315/4/2026
This study investigated sex-specific differences in thoracic injury prevalence, causation, and rib fracture patterns among seriously injured occupants in frontal motor vehicle collisions. Crash Injury Research and Engineering Network (CIREN) data from 2005 to 2022 included 793 front-seat occupants aged 16 years and older with Abbreviated Injury Scale 2+ thorax injury, representing 1802 thoracic injuries. Injuries were grouped as rib fracture, sternum fracture, hemo/pneumothorax, lung injury, heart injury, and other. A weighted scoring system captured contributions of involved physical components to each injury. Logistic and linear regression with generalized estimating equations assessed sex associations with injury presence and causation. Two models were estimated: a comprehensively adjusted model including demographic, crash, vehicle, restraint, and airbag deployment, and a simplified model adjusting for age, body mass index, delta-V, and occupant role. Among occupants with AIS 2
Armstrong, William, Devane, Karan, Hsu, Fang-Chi, Heilmann, Nina, Sink, Joel, Miller, Anna N., Kiani, Bahram, Martin, R. Shayn, Stitzel, Joel D., Weaver, Ashley
Assessing the Influence of Reclined Vehicle Seatback Configurations with and without a Belt-Positioning Booster on Child Posture via Pressure Mapping09-14-01-00045/4/2026
Objective: This study sought to implement pressure mapping methodology to assess variation in children’s center of force positions in reclined vehicle scenarios. Methods: Thirty-four children between 4 and 12 y (8.1 ± 2.0 y) were statically evaluated on a vehicle seat across two seating conditions (with and without a backless booster) and three seatback recline conditions (25°, 45°, and 60°). Center of force was recorded using pressure sensors attached to the seating surface. Average center of force fore/aft positions were calculated and transformed into the vehicle coordinate system using 3D coordinate measurements. Descriptive statistics and repeated measures ANOVA were used to assess variation in center of force position across seating and recline conditions, with subject included as a random effect. Results: Center of force fore/aft position varied (p < 0.05) with recline condition, seating condition, and the recline/seating condition interaction term. On the booster, the average
Baker, Gretchen H., Connell, Rosalie R., Graci, Valentina, Mansfield, Julie A.
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