Browse Topic: Human Factors and Ergonomics
Military ground vehicles are transitioning from manually operated platforms to highly automated systems, which fundamentally alters the cognitive demands placed on crew members. Rather than reducing workload, automation frequently redistributes it, introducing challenges associated with supervisory monitoring, autonomy mode calibration, and situational awareness. Augmented cognition (AugCog) offers a closed-loop framework in which real-time physiological and behavioral measures of operator cognitive state can be used to dynamically adapt system interfaces and autonomy levels. This paper reviews six nonintrusive sensor modalities suitable for military ground vehicle crew stations: remote photoplethysmography (rPPG), facial thermography, eye tracking and pupillometry, dry-electrode electroencephalography (EEG), Facial Action Coding System (FACS) action unit (AU) analysis, and elastic electrodermal activity (EDA) sensors. A conceptual multimodal crew station integration framework is proposed, and future research directions are outlined.
Modern mission-critical ground vehicle systems must adapt to rapidly evolving threats, deploying changes in months or days while maintaining reliable and safe operation. Historic manual development and testing methods cannot keep pace without compromising safety assurances. Continuous Integration and Continuous Deployment (CI/CD) pipelines offer proven approaches to accelerating development, but implementing them for mission-critical systems requires careful attention to verification rigor. This paper presents a practical framework for implementing CI/CD pipelines across any level of rigor, from rapid prototyping to DO-178C and ISO 26262 certified systems. Drawing on experience from aviation, medical device, and ground vehicle development, the framework provides guidance for each pipeline stage based on the system’s desired level of rigor. This framework includes an examination of the value of Software-in-the-Loop vs Hardware-in-the-Loop testing to optimize development timelines while maintaining software quality.
Ground Vehicle Systems Center (GVSC) conducted a Soldier Touch Point (STP) in the field comparing the use of Vitreous User Interface (UI) on a Helmet Mounted Displays (HMD) to a Soldier Machine Interface (SMI) on Vehicle Mounted Displays (VMD). Soldiers drove a Stryker Vehicle equipped with 360-degree indirect vision through a series of mobility obstacles at Camp Grayling. No significant differences were found in Soldier performance between the UI conditions, however, a significant performed better maneuvering through obstacles on the right-hand side of the vehicle in comparison to the left. This is a continuation of simulation only work previously presented at GVSETs 2023.
Biomanufacturing uses microorganisms to produce chemicals or materials of interest, much like a brewery uses fermentation by yeast to produce the alcohol in beer. Biomanufacturing relies upon synthetic biology to reprogram yeast or other microorganisms to produce something of greater value, such as fuel, food, or pharmaceuticals. Industrial biomanufacturing has made significant advances and the products it can deliver include reactive coatings and textiles, sensors, optical materials that can bend light, and new therapeutics such as antimicrobials and vaccines. The convergence of synthetic biology, robotics, and artificial intelligence is opening the way to produce materials never before possible in the commercial market. These same technologies create the opportunity for the miniaturization of this technology to fit into ever more compact spaces, bringing forward deployment of these mini-factories closer and closer to the point of need.
This SAE Recommended Practice is intended to establish a procedure to certify the low mu/winter driving skill levels of professional drivers. This certification can be used by the individual driver to qualify their skills when seeking employment or other professional activity. These certification levels may also be used by test facilities or other organizations when seeking test or professional drivers of various skills. This document provides directions for obtaining certification through Probitas Authentication®1 and the low mu/winter driving skill examination requirements. This document is a supplement to SAE J3300, providing information specific to the low mu/winter driving skill certification and clarifying the application of the rules set forth in SAE J3300 to the low mu/winter driving certification. While the references, definitions, rules, and guidelines presented in SAE J3300, Sections 1 through 5 apply to the low mu/winter driving certification, they are not repeated in this document.
The global automotive industry is facing an unprecedented convergence of uncertainties driven by geopolitical tensions, evolving trade policies, emissions related regulations, and increasingly volatile consumer demand. Shifting emissions legislation, including the EU’s tightened CO2 targets and long-term plans to phase out internal combustion engines, is imposing strategic and financial pressures on automakers and suppliers as they navigate divergent regional regulatory trajectories. Demand side volatility further complicates the landscape. Consumer preferences are fluctuating due to economic pressures, infrastructure constraints, and uneven EV adoption patterns. While some markets show stagnation in battery electric vehicle uptake, hybrids are rising as consumers seek cost efficient alternatives amid uncertain energy and regulatory environments. Within this unstable context, the transition toward Software Defined Vehicles (SDVs) is emerging as a critical strategic response. SDVs, characterized by centralized computing, updatable software architectures, and over the air feature deployment, offer automakers greater adaptability in addressing regulatory shifts and market dynamics. By decoupling hardware from software cycles, SDVs enable faster innovation, reduced development risk, and new digital revenue models, while virtualization and AI driven analytics enhance development efficiency and lifecycle value.
This study compares two international loudness standards—International Organization for Standardization (ISO) 532-1:2017 (Zwicker) and ISO 532-3:2023 (Moore–Glasberg–Schlittenlacher)—for assessing vehicle wind noise using wind tunnel measurement data. The two methods demonstrate good agreement in ranking wind noise quietness at typical highway speeds (120–140 km/h). However, discrepancies arise under specific conditions due to ISO 532-3’s binaural processing, which accounts for interaural inhibition effects. These differences are particularly pronounced in vehicles with asymmetric wind noise levels between the driver and passenger sides. Power-law regression analysis reveals that binaural loudness at the driver side (ISO 532-3) increases at a slower rate with wind speed compared to the monaural measurements [driver outboard ear (DOE)] of ISO 532-1. Under yaw angle conditions, the perceptual contribution of the driver inboard ear (DIE) introduces subtle metric-dependent variations. Contribution analyses further highlight method-specific sensitivities to noise source location and direction. Overall, this study provides a valuable reference for implementing loudness metrics in automotive wind noise engineering.
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.
To accurately assess the navigation safety status of LNG vessels in port waters and balance safety control with waterway capacity efficiency, this study constructs a 3D dynamic safety domain model for port LNG vessels, integrating human–ship–environment multi-factors. The model introduces the Weibull function to quantify the impact of drivers’ knowledge, skills, and physiological-psychological states on safety boundaries, combines a ship motion mathematical model to establish a 2D safety domain boundary equation, and incorporates hull subsidence to build a vertical dimension, forming a complete 3D model. Longitudinally, the safety distance is calculated using the car-following braking theory, while laterally, boundaries are determined by controlling the ratio of inter-vessel interference force to navigation resistance. Through static scenario analysis and dynamic simulation verification, results show that the safety domain scale is dominated by ship speed and environmental conditions, and its shape tends to shrink as the driver’s state improves, making it more suitable for actual port scenarios than traditional models. Verified with a specific LNG hub port as a case, the safety distance calculated by the model is significantly reduced compared with current specifications, while the delay impact rate and average delay time on other vessels are decreased. The research results establish a quantifiable framework for dynamic safety assessment, providing maritime administrations and on-board pilots with a scientifically-grounded tool to determine real-time safe navigation boundaries in complex port environments, balancing safety control with operational efficiency.
Under the constraints of conventional chassis layouts, traditional wheeled vehicles struggle to maintain stable obstacle-crossing performance on complex terrain. This study aims to enhance both the obstacle-crossing capability and stability of such vehicles. First, a transformable wheel capable of varying its effective radius and actively adjusting the wheel–ground contact configuration is designed, and its degrees of freedom are analyzed using screw theory. Next, based on screw theory and Lie group theory, position-level and velocity-level kinematic models of the transformable wheel are established, and system-level performance indices—including workspace, singular configurations, and force-transmission characteristics—are formulated. Finally, taking these performance indices as optimization objectives, a constrained optimization model of the mechanism’s geometric parameters is constructed, from which an optimal dimension set for the transformable wheel is obtained. The results show that the optimized transformable wheel has significantly improved minimum singularity and dexterity. The designed transformable wheel can achieve changes in wheel radius and wheel rim inclination angle, improving the vehicle's passability in complex terrain.
Every kid who has read a comic book or watched a Spider-Man movie has tried to imagine what it would be like to shoot a web from their wrist, fly over streets, and pin down villains. Researchers at Tufts University took those imaginary scenes seriously and created the first web-slinging technology in which a fluid material can shoot from a needle, immediately solidify as a string, and adhere to and lift objects.
With the increasing demand for material microimaging analysis, there is a growing need for advanced precision grinding and polishing equipment, especially for metals, ceramics, and composites. Existing automated systems struggle with handling complex material challenges. This paper presents a fully automated adaptive grinding and polishing machine based on an STM32 microcontroller that handles multi-material samples. The system includes modules for sample access, cleaning, pad replacement, human-computer interaction, and equipment communication. The STM32 microcontroller executes grinding and polishing tasks based on instructions from the host computer while dynamically adjusting PID control parameters using an improved weighted average optimization algorithm. This approach enhances control accuracy, stability, and overall surface treatment quality compared to traditional PID control methods.
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