Browse Topic: Human Factors and Ergonomics
Long-term orbital missions require highly independent life-support systems, maintaining ecological stability under limited external support and subsystem attenuation. Conventional strategies are typically based on fixed threshold rules or deterministic mass-balance models and cannot adapt to disturbances or multi-objective trade-offs between resource safety and environmental load. This paper proposes a reinforcement learning framework for managing micro closed-loop ecological systems under reliability decay and environmental constraints. A reinforcement learning controller based on Proximal Policy Optimization (PPO) is trained to learn stable regulation policies with random disturbances. A dynamic state model is constructed to describe the coupled and time-sequential elements, ranging from water storage, oxygen concentration, energy reserve, subsystem reliability to ecological load. Degradation propagation is integrated into the transition dynamics through reliability-dependent recycling efficiency. Simulation experiments demonstrate that the proposed policy maintains all resource variables within the safety margins while reducing ecological imbalance compared with traditional strategies. Consequently, the proposed framework provides an expandable control architecture for independent regulation of space station life-support systems.
Youth bicycle helmet manufacturers often add shell protrusions to make helmets more attractive or fun for children, yet the safety implications of these features are not well understood. While prior work suggests protrusions may affect head impact kinematics, no study has evaluated their effectiveness in location-matched impacts between helmets with and without protrusions. Twelve youth bicycle helmet models, with protrusions intact and removed, underwent matched oblique impacts at three locations and 4.2 m/s to capture resulting peak linear acceleration (PLA) and peak rotational acceleration (PRA). A linear mixed model was used to quantify the effect of protrusion presence on PLA, PRA, and impact duration. The youth bicycle helmet models produced a wide range of kinematics. Protrusion presence had a strong effect on PLA, PRA, and impact duration. PLA averaged 103.0 ± 22.8 g for helmets with protrusions compared to 143.9 ± 21.4 g for helmets without protrusions, while PRA averaged 4432 ± 1570 rad/s2 for helmets with protrusions and 5177 ± 2110 rad/s2 for helmets without protrusions. These findings suggest that helmet protrusions can reduce peak head accelerations in youth bicycle helmet impacts.
Modern combat helmets improve wearer survivability through preventing ballistic penetration via delamination or deformation of the shell material. However, this deformation may impinge upon the skull and present a risk of behind-helmet blunt trauma (BHBT). While legacy aramid helmets from the late 1970s–1980s inform current NIJ testing standards, the advent of lower areal density ultra-high molecular weight polyethylene (UHMWPE) and modern suspensions may incur unknown changes that present an unknown effect on BHBT risk. This study investigates whether current standards relying on a peak acceleration threshold and residual clay deformation may not reflect changes in deformation geometry seen in newer shell materials and suspension designs. Thirty-eight helmets categorized into three groups, older aramid, newer aramid (with new suspension), and prototype UHMWPE (with old suspension), were mounted on Hybrid III ATD head-necks and impacted on the temporal surface with 9 mm NATO projectiles at velocities between 388 and 482 m/s. Flash x-ray imaging captured deformation geometry. Deformations were digitized to measure maximum depth, volume, and surface area recruited. Multiple linear regression identified the influence of shell material and suspension on geometry. Results indicated that shell material significantly affected deformation volume and area (p < 0.05). Notably, UHMWPE exhibited a qualitatively more “pointed” deformation profile compared to aramid, recruiting material differently as depth increased. In contrast, suspension type and helmet design did not significantly influence deformation geometry. These findings suggest that the BHBT geometry in UHMWPE helmets differs fundamentally from aramid helmets. As UHMWPE helmets encounter higher-energy threats, current acceleration threshold or depth-based standards may not fully capture the risk of skull fracture. To future-proof helmet validation, testing standards should evolve beyond current standards to include area recruitment and other geometric measures.
To satisfy the real-time beam tracking requirement of low earth orbit (LEO) satellite ground terminals under highly dynamic pass conditions, this paper proposes a three-state hierarchical state-machine beam-control algorithm for liquid crystal phased array antennas (LCPAs). The tracking process is divided into three stages. S1 coarse nine-point acquisition is used to rapidly cover a wide pointing-uncertainty region. S2 fine nine-point refinement introduces quadratic-surface fitting to obtain local peak estimation at sub-step resolution. S3 predictive tracking adopts an interacting multiple model Kalman filter (IMM-KF) based on the constant-acceleration (CA) model and the Singer model, and designs an adaptive covariance regulation mechanism for both measurement and process noise. Combined with explicit delay compensation for liquid-crystal response time, the method suppresses pointing lag and error accumulation in high-dynamic intervals. A dual-threshold hysteretic loss-of-lock criterion and a filter-reset mechanism are also integrated to guarantee autonomous link recovery. Simulation results show that, in an LEO pass scenario with a maximum angular rate of about 2 °/s, the proposed method reduces the median 2D RMSE by about 52%, reduces the 90% quantile error by about 54%, and lowers the median average power loss from 0.14 dB to 0.03 dB compared with the traditional scheme.
In addressing the challenges of deep purification of cadmium (Cd) heavy metal contamination and membrane fouling control in spacecraft drinking water sources and recirculation systems, this study adopts a coagulation-ultrafiltration coupled process, with polyaluminium chloride (PACl) as the coagulant and sodium polyacrylate (PAANa) as the complexing agent. A systematic investigation was carried out to examine the effects of key operating parameters—including coagulant dosage, complexing agent dosage, and humic acid (HA) concentration—on Cd removal efficiency, floc morphological characteristics, and ultrafiltration membrane resistance distribution. The results indicate that for simulated raw water containing 0.05 mg/L Cd and (50 ± 0.5) NTU turbidity, under the optimized conditions of 20 mg/L PACl, 20 mg/L PAANa, and pH = 7, the Cd concentration in the effluent treated by the coagulation-ultrafiltration coupled process is reduced to as low as 0.004 mg/L, which meets and even exceeds the hygiene standard limits for both spacecraft drinking water and domestic drinking water. HA was found to promote floc growth and enhance the complexation-based removal of Cd, yet it exacerbates membrane surface adsorption and gel layer fouling. Membrane resistance analysis reveals that gel layer resistance and concentration polarization resistance are the primary sources of fouling, and membrane fouling can be effectively mitigated through rational regulation of operating parameters. This coagulation-ultrafiltration coupled process is characterized by high purification efficiency, stable effluent quality, and strong modularity. It is well adapted to the requirements for closed-loop circulation of spacecraft water resources and drinking water safety assurance, and can provide technical support for water circulation systems in manned spacecraft, drinking water purification at launch sites, and in-situ water treatment during deep space exploration.
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.
The gathered journalists cover their ears as a loud hydraulic ram begins to load and a warning alarm sounds. Less than a minute later… FOOSH… BAM! A 9.9-pound model of a human head is launched into the front-end structure of a test vehicle, deforming the hood and sending the head bouncing to the ground. The violence of the moment, which is part of pedestrian safety research, is a stark reminder of the seriousness of all the testing that happens at Toyota's North American Research and Development Headquarters in York Township, Michigan. The $187-million (in 2007 dollars) facility includes 180,000 sq.ft. of research and testing space.
Aumovio, working with sensor-maker trinamiX, has developed a solution to detect a driver's blood alcohol content (BAC) with a non-invasive finger touch. The race to develop systems to prevent alcohol-impaired driving has seen many different solutions proposed, from passively sensing the breath of a driver to analyzing micro-movement of the steering wheel. Aumovio says its system detects BAC with the accuracy of the drawn-blood tests, which have been proven to be more accurate - and less prone to false positives -- than breath or urine tests.
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