Browse Topic: Safety

Items (21,422)
Commercial photogrammetry software packages have been extensively validated for accident reconstruction applications, and these software packages are widely used to measure physical evidence such as roadway evidence, vehicle crush profiles, and vehicle speeds from videos. While effective, these tools rely on proprietary licenses and subscription models that can pose financial barriers for some users, particularly law-enforcement agencies and smaller institutions. Blender, using the CamMatch add-on, is used to solve camera intrinsics, including lens distortion parameters, as well as the camera position and orientation for reverse-projection photogrammetry workflows. CamMatch generates a virtual camera that is correctly positioned and oriented within the 3D scene, which is then used to overlay the undistorted video directly onto the scene. This alignment enables reverse-projection analysis from which vehicle position and speed can be determined. Data from SAE Paper 2025-01-8700 was used, where vehicle speeds were calculated by utilizing the footage recorded by front, left repeater, right repeater, and back cameras of Tesla Model 3 and Tesla Model Y vehicles. In the reference study, GPS-instrumented target vehicles equipped with Racelogic VBOX systems traveled across each camera’s field of view at speeds ranging from 7.2 km/h to 20.4 km/h. Video footage was retrieved via direct USB download from the subject Tesla vehicles. Our study utilized reverse-projection photogrammetry with Blender, using cameras generated by CamMatch with point cloud representations of both the test environments and target vehicles used to establish 3D reference geometry. Vehicle speeds determined from this process exhibited an error (mean ± SD) of 1.84 ± 1.15% across 25 tests compared to an error of 2.10 ± 1.63% calculated in PhotoModeler. Moreover, the maximum difference between the VBOX data and the calculated speeds among all the results was found to be 0.53 kph. These findings support the use of CamMatch as an open-source tool for photogrammetry with capabilities comparable to the established photogrammetry methodologies.
Farhat, Ali, Cornetto, Anthony, Faust, Mason, Miloszewski, Zoe, Engebretson, James
Conventional types of wipers are characterized by some consistent disadvantages, such as huge uncleared blind spots (up to 40 percent of the target area), limited wiping functionality, and great dynamic visual interference. Due to the intensive full-field visibility demands of autonomous driving, this paper will introduce a new linear reciprocating wiper that will be driven by a ball screw. In particular, one of the prototypes of such a system is designed based on a Dongfeng heavy-duty truck, according to which the traditional oscillatory movement is converted into a horizontal directional movement by a ball screw. This is powered by a motor of 24 V drive with a worm gear reducer to give the force needed to achieve the horizontal reciprocating motion of the wiper blade assembly over the windshield. For the intelligent control module of the proposed lateral linear wiper system, a special intelligent control system is developed based on the principle of CAN bus communication and multi-sensor fusion. Both a rain sensor and a proportional-integral-derivative (PID) algorithm allow the system to achieve adaptive control of wiper speed and apply to various modes, including intermittent wiping, low-speed wiping, and high-speed wiping.
Dong, Xingzhuang, Hu, Yanxingyu, Li, Jincheng, Xu, Tongqiang, Wu, Liying
During cornering-braking maneuvers, an excessively high braking torque can consume a substantial portion of the available tire-road friction and cause insufficient frictional capacity to satisfy the lateral force demand generated by cornering. As a result, the vehicle may experience stability degradation and, in severe cases, lose control, potentially causing accidents. In this study, an AMESim-based vehicle dynamics model is developed, and yaw rate and sideslip angle are adopted as the primary evaluation indices to characterize steering-braking behavior. Under conditions of a fixed turning radius and initial braking speed, the critical braking force was simulated and analyzed. Additionally, the critical steering wheel angle was examined under conditions of a fixed braking torque and steering speed. The results indicate that if either the braking force or the steering wheel angle exceeds its critical value, the vehicle will lose stability during combined steering and braking.
Ma, Lianglin, Yi, Bingjun, Hu, Yang
Low-altitude economy has already become an important strategic engine for high-quality development as a symbol of new productive forces. The impact of ESG performance on corporate value within the low-altitude economy (a strategic emerging industry), as well as its dual effects and situational specificities, is systematically and empirically examined in this paper using panel data from Chinese A-share listed companies from 2018 to 2023. The results show that the ESG performance of “low-altitude economy” enterprises has a significant impact on company value through two channels: investment in R&D and obtaining more government subsidies. Analyst coverage might be contradictory; too much analyst coverage may even counteract the advantage of ESG performance. Our results also reveal significant heterogeneity patterns. Value-enhancing effects of ESG are greater in low-pollution sectors, technology-based enterprises, non-State-owned companies, and companies located in central and western China. To foster sustainable, high-quality company business, this paper provides suggestions for implementing ESG and conceptually elaborates on how the low-altitude economy influences company ESG performance.
Lv, Xiaonuo, Chu, Yanchang
Low-altitude networks, which support communication among ground stations and aerial nodes such as UAVs, require real-time monitoring to ensure reliable operations under dynamic conditions. The highly mobile nature of UAVs, coupled with frequent topology changes and limited onboard resources, presents unique challenges for network monitoring. In-band Network Telemetry (INT) provides a promising approach to monitor low-altitude networks by embedding telemetry metadata directly into data packets, enabling fine-grained visibility into network behavior. However, traditional INT schemes introduce substantial bandwidth overhead, a critical issue for resource-constrained low-altitude links. Furthermore, existing optimization approaches typically rely on static configurations, which cannot effectively handle the highly dynamic and volatile conditions we observe in low-altitude network environments. We present MGAT (Multi-Granularity Adaptive INT), a lightweight telemetry mechanism for low-altitude networks that achieves efficient monitoring through decoupling control decisions from data collection operations. Our data plane design exploits the spatiotemporal characteristics of different telemetry data types through three specialized collection schemes: flow-level aggregation is used for statistical metrics, static attribute sampling handles time-invariant properties, and packet-level extremum tracking captures critical outliers. The control plane combines QoS-aware flow classification with load-adaptive sampling, allowing the system to dynamically adjust monitoring intensity according to real-time network utilization. We evaluate MGAT through experiments and find that it reduces overhead by 98.7% compared to traditional INT while maintaining high detection accuracy (F1-score of 0.965). When network load varies dynamically, MGAT demonstrates 8.3% higher accuracy than static baseline methods and consumes 11.8% less bandwidth, confirming its ability to adapt effectively to the complex dynamics of low-altitude networks.
Wu, Zongyan, Hu, Jinju, Liu, Kang, Liu, Ying
As the use of low-altitude drones in urban environments continues to grow, the likelihood of near-miss events and collisions between birds and drones operating in shared airspace has drawn increasing attention. To address this issue, this paper proposes a collision probability assessment framework based on the Boids swarm behavior model and Monte Carlo statistical methods, using the Chengdu silky-tailed starling as a case study: simulating the relative motion between bird flocks and UAVs within typical flight segments, defining near-misses and physical collisions events based on minimum separation distance thresholds, and employing Wilson confidence intervals to quantify uncertainty and analyze convergence. The simulation results indicate that after introducing the detectionavoidance mechanism, the minimum distance distribution function curve shifts rightward overall, collision duration is significantly reduced, the probability of event occurrence is effectively lowered, and the cumulative estimate exhibits good convergence under large samples. Additionally, the probability of incidents exhibits a monotonically decreasing trend with enhanced detection capabilities, revealing a monotonically sensitive characteristic where higher detection capabilities reduce collision probability risks. This provides a quantitative basis for low-altitude planning and risk management.
Pan, Anqi, Long, Yong, Li, Xiaojing, Chen, Di, Yang, Jibo, Zhao, Jinchen, Wu, Honggang
The integration technology of autonomous navigation and positioning provides critical technical support for high-precision positioning in the marine environment. As an indispensable core technology in modern marine navigation, satellite navigation plays a vital role in marine navigation safety and precision operations, such as marine surveying, ship navigation, and offshore engineering. The BDS PPPB2b service is commonly used in the marine high-precision application. However, compared to the landing application, the BDS PPP in the marine environment performs poorly due to the complex environmental factors on the ship-borne platform, such as hull occlusion and sea surface signal reflection. To compare and analyze the positioning performance differences of BDS PPP-B2b between shore-based and ship-borne platforms, an experiment has been conducted by using real data of the BDS receiver on both shore-based and ship-borne platforms. The results have shown that the BDS PPPB2b positioning performance on a ship-borne platform achieves poor satellite visibility and stable positioning performance. The BDS PPPB2b positioning accuracy after convergence can reach centimeter and decimeter levels on shore-based and ship-borne platforms, respectively.
Wang, Xilong, Li, Menghao, Shi, Huiwen, Sun, Min, Lu, Yin
In recent years, Reinforcement Learning (RL) has been increasingly applied to the collision avoidance systems of Unmanned Aerial Vehicles (UAVs) due to its high performance in complex tasks and relatively low online computational cost. Despite these advantages, the lack of interpretability in RL and decision-making processes poses significant challenges to safety verification, which severely limits the practical deployment of RL-based autonomous flight systems in safety-critical scenarios. Ensuring safety during both training and testing remains the key for real-world applications. To address this issue, a Run Time Assurance (RTA) filter framework for a UAV collision avoidance system based on RL is proposed. The framework continuously monitors the avoidance actions generated by RL and ensures that unsafe actions can be identified and corrected in real time. The framework provides security while retaining the performance advantages of RL. First, a discrete kinematics model of the UAV and a collision avoidance environment for a three-dimensional multi-intruder UAV are established. The Proximal Policy Optimization (PPO) algorithm is used to train the UAV avoidance policy. Secondly, the RTA filter with safe constraints is designed based on this model. To reduce the position error between the discrete kinematics model and the continuous dynamics model of the UAV, optimization is performed using the Sequential Least Squares Programming Method (SLSQP). The RTA is applied to the training and testing phases of UAV collision avoidance systems to monitor and correct unsafe actions online. Finally, three training and testing methods are set: no RTA, RTA without punishment, and RTA with punishment. Comparing different relaxation coefficients allows for analyzing their impact on filter performance. Simulation results demonstrate that the RTA effectively enhances safety throughout training and testing. Compared with the no RTA method, the collision rate is reduced by 7.04%, and the success rate is increased by 2.68%. In extreme collision avoidance scenarios, the average collision rate obtained by different reinforcement learning algorithms is reduced by 21.46%, and the average success rate is increased by 15.54%.
Ma, Zan, Yan, Liqin, Bai, Jie, Liu, Yubin, Sun, Shuguang
With the rapid development of civil unmanned aircraft systems (UAS), their operating scenarios are becoming more and more complex. The operation mode of one pilot controlling one or more unmanned aircraft has been unable to meet the needs of specific scenarios, such as logistics scenarios. Distributed operation has gradually become the future development trend of UAS in these scenarios. This paper expounds the theoretical basis, structural framework, and implementation path of the grading of the distributed operation level. In this paper, the evaluation framework is established by using the two dimensions of system automation level (AL) and safety assurance (SA) when grading the operation level (OL), and the evaluation of the operation level is supported by standardized test methods. The establishment of the method in this paper can fill the gap in the operation and management of drones, and provide a basis for operators to apply for operating licenses and for government supervision.
Ma, Mengdi, Tian, Lingling
Unmanned aerial vehicles (UAVs) equipped with chemical contaminant sensors offer an innovative approach for rapid and safe remote chemical reconnaissance. However, the proliferation of diverse UAV platforms presents a critical challenge: how to select the optimal platform for a given mission scenario. This paper establishes a systematic suitability analysis framework for deploying chemical contaminant sensors on three mainstream UAV platforms-multirotor, fixed-wing, and vertical take-off and landing (VTOL) types. We analyze payload capacity, endurance, flight stability, environmental adaptability, and mission system integration. To reduce decision subjectivity, we develop an Analytic Hierarchy Process (AHP)-based quantitative evaluation model incorporating expert surveys and consistency tests to validate the weighting process. Beyond the evaluation framework, we explore key engineering challenges in platform-sensor integration, including aerodynamic interference, vibration and electromagnetic compatibility, and power management. We compare quantitative measurements and qualitative features across platforms in simulated mission scenarios. The resulting selection criteria provide a theoretical basis and a reproducible decision-support framework for developing chemical detection systems applicable to emergency response, environmental monitoring, and public safety.
Liang, Ting, Wen, Hao, Qi, Yelin, Yang, Wen
In autonomous driving and advanced driver-assistance systems (ADAS), radar sensors play a crucial role in detecting and tracking objects under diverse environmental conditions [1, 2, 3]. One persistent challenge is the accurate representation of long vehicles, such as trucks and buses, whose extended radar signatures often result in a wide spatial spread of detections with similar radial velocities, making association difficult due to gating limitations. The GRID component processes raw radar measurements to generate occupancy grids and extract candidate targets, including stationary environmental structures [4, 5]. In the case of stationary long vehicles, multiple stationary objects may overlap with grid-based environment targets, allowing them to be consolidated into a single tracked object. This paper presents a novel approach for radar object merging and retention decision-making using fuzzy logic to distinguish between true moving and stationary objects in the presence of GRID targets and object association mechanisms. The association modules link radar measurements or detections, when available, with existing tracks to maintain temporal consistency, enabling the formation of radar objects represented by track points. The proposed method fuses radar objects based on their radial velocity and spatial overlap, while a fuzzy logic–based decision engine evaluates object persistence. The approach improves object continuity and reduces false positives in driving functions such as Blind Spot Detection (BSD), Emergency Brake Assist (EBA), and Adaptive Cruise Control (ACC). Simulation and real-world validation results demonstrate significant improvements in object tracking accuracy, particularly for long vehicles in urban environments.
Mohanty, Sanket, Sarkar, Sanglap
As automotive architectures evolve toward Software Defined Vehicles (SDVs) and high levels of driving automation, traditional safety analysis techniques rooted in hardware reliability require significant adaptation. The Classical Event Tree Analysis (ETA), a cornerstone of ISO 26262 functional safety compliance, relies on static, binary branching logic where each function either fails or succeeds. While highly interpretable and effective for modelling random hardware failures, classical ETA struggles to capture the dynamic, non-linear interactions, temporal degradation, and complex human-machine interface (HMI) dependencies that are characteristic of modern Advanced Driver Assistance Systems (ADAS) and autonomous vehicles. This paper proposes State Dependent Event Tree Analysis (SD-ETA), a methodological extension designed to integrate discrete state vectors and temporal dependencies into the classical ETA framework. SD-ETA assigns probabilities to the branches for the dynamic nonlinear interactions, temporal degradation, and complex human-machine interface (HMI) dependencies instead of binary values, thereby allowing the system state (comprising vehicle physics, environmental conditions, and driver attention metrics) to dynamically update based on the outcomes of the preceding nodes. This approach retains the visual hierarchy and regulatory familiarity of standard event trees while significantly enhancing model fidelity for Safety of the Intended Functionality (SOTIF) scenarios governed by ISO 21448. To demonstrate the necessity and utility of this methodological evolution, this paper presents a comparative case study analysing a system operating under degraded environmental conditions. The quantitative application reveals that while classical ETA predicted a relatively low collision risk by treating sensor performance as a static binary state, the dynamic SD-ETA simulation exposed a critical hidden safety gap, calculating a higher collision probability due to compounded latency and degraded physical operating parameters. Ultimately, SD-ETA equips safety practitioners and automotive regulators with a modernized, time-aware framework to accurately evaluate the complex, interacting risks of autonomous systems without sacrificing the transparency required for rigorous safety certification.
Sharma, Dhiraj Mohan, Mutagi, Megha, Reddy, Kakarla Subba
The transition toward Software-Defined Vehicles (SDVs) [1] is driving a fundamental shift in automotive electrical and electronic architectures [1], where centralized high-performance computing platforms must support mixed-critical workloads under strict requirements for determinism, performance isolation [2], and functional safety. Consolidating safety-critical and non-critical applications onto shared System-on-Chip (SoC) platforms [3] introduces significant challenges in ensuring predictable execution behavior, bounded latency, and compliance with safety standards [4, 15]. Addressing these challenges is essential for enabling scalable and reliable next-generation automotive systems [1] [5]. This paper presents a hardware–software co-design approach to achieve deterministic and safety-certified operation in SDV [1] architectures. Unlike traditional implementations that rely on software hypervisors or hardware isolation independently, the novel core contribution of this work is an integrated, dual-layer hardware-software orchestration model. It dynamically coordinates static Stage-2 translation with hardware Extended Resource Domain Controllers (XRDC) and Memory Partitioning and Monitoring (MPAM) to enforce end-to-end spatial, temporal, and interconnect-level bus isolation. The proposed solution combines hardware-assisted resource isolation mechanisms, including Hardware-enforced resource isolation and Memory Partitioning and Monitoring (MPAM) [6], with a lightweight partitioning hypervisor and Virtual Machine Monitor (VMM). XRDC [7] provides fine-grained access control for memory and peripheral resources, while MPAM [6] enables memory bandwidth allocation and monitoring to minimize resource contention across competing workloads. On the software side, the partitioning hypervisor [8] enforces strong temporal and spatial isolation between Virtual Electronic Control Units (vECUs), allowing mixed critical applications to coexist safely on a shared platform. VMM supports efficient virtualization [9, 10] and lifecycle management of virtual machines while maintaining deterministic execution characteristics. The proposed architecture aligns with the requirements of ISO 26262 [4], enabling the certification of safety critical applications alongside non-critical services. By integrating hardware-enforced isolation with software-level partitioning, the approach ensures predictable system behavior and reduces interference between workloads. The results demonstrate that a coordinated hardware–software strategy is essential to bridge the gap between high-performance computing and functional safety, thereby enabling scalable, deterministic, and safety-compliant SDV [1] platforms for future automotive applications. System-level validation conducted on an NXP S32G3 [7] [10] vehicle network processor platform demonstrates the efficacy of the proposed co-design. Under artificial memory-bus contention generated by background non-critical (QM) Linux traffic, the hardware-enforced MPAM bandwidth regulation reduced maximum worst-case execution time (WCET) jitter for an ASIL real-time control loop from 142.6 μs down to 8.4 μs—achieving a 94.1% reduction in latency variation. Paravirtualized hypercall operations achieved a 40.2% latency reduction compared to standard Trap-and-Emulate approaches.
Khan, Misbah Ullah
The rapid evolution of automotive electronics has pushed traditional vehicle electrical and electronic (E/E) architectures to their limits. Conventional designs, characterized by point-to-point wiring harnesses, distributed domain-specific ECUs, and communication buses such as LIN, CAN, and Ethernet, impose significant drawbacks in terms of vehicle weight, integration complexity, and long-term scalability. As the industry moves toward the Software-Defined Vehicle (SDV) paradigm, there is a compelling need to rethink the foundational principles governing in-vehicle connectivity. This paper proposes a wireless-centric SDV architecture in which non-functional-safety-relevant sensors and actuators communicate over standardized wireless protocols, eliminating the need for their associated physical wiring. By decoupling these peripheral nodes from the wired backbone, the proposed architecture reduces harness bulk, lowers vehicle mass, minimizes redundant compute hardware, and significantly reduces integration cost. Safety-critical systems including those governing powertrain, braking, and steering are explicitly retained on hardwired, deterministic communication channels in compliance with ISO 26262 functional safety requirements. This paper additionally defines explicit assumptions and fallback behavior governing that wired/wireless boundary. The architectural framework is evaluated against key SDV design objectives such as modularity, over-the-air (OTA) updateability, and feature scalability, assessed qualitatively against published engineering precedent, with a structured validation roadmap defined to quantify latency, reliability, and coexistence performance in follow-on work. The analysis demonstrates that a hybrid wired-wireless topology can substantially simplify vehicle E/E architecture while maintaining the reliability and latency guarantees demanded by automotive-grade systems. This work contributes to a structured transition roadmap for OEMs and Tier-1 suppliers seeking to adopt SDV principles without compromising vehicle safety or regulatory compliance, together with an explicit protocol-selection framework and a functional-safety argument for the wired/wireless boundary.
Hebbale Ramkumar, Ramya, Sarkar, Dibas
Automotive radar systems do not authenticate the signals they receive, allowing an external transmitter to create phantom objects that can trigger automatic emergency braking (AEB). This paper quantifies the threat using real radar measurements from the public RadarScenes dataset and evaluates a software countermeasure that requires no hardware modification. Computer-generated phantom radar returns were added to 200 motorway sequences and adjusted so the OS-CFAR detector accepted them as real objects. In the undefended system, radar detections were tracked as obstacles and braking was initiated when an object appeared within 30 m, resulting in unnecessary braking in 87.0 percent of attacked sequences. The proposed two-layer filter combines kinematic plausibility gating with camera-radar cross-validation. Layer 1 checks track history and physical movement over three consecutive frames, while Layer 2 reduces confidence when a clear-weather radar detection lacks camera confirmation. With both layers active, false braking fell to 3.5 percent, with no genuine detections missed across 200 genuine sequences. SHAP analysis of a Random Forest classifier identified kinematic implausibility as responsible for 62.3 percent of correct suppressions and produced a machine-readable evidence record to support cybersecurity documentation under ISO/SAE 21434 and safety documentation under ISO 21448. These results apply to an offline replay experiment using synthetic injections. Validation with real attack hardware, synchronized camera data, and vehicle testing remains future work.
Sehgal, Vishal, Sekaran, Nikhil
Autonomous Emergency Braking (AEB) is a safety-critical Advanced Driver Assistance System now mandated for commercial vehicles in India.to reduce crash frequency and severity. This paper presents a structured, simulation-based V&V approach for camera-based AEB that integrates TTC braking evaluation, Forward Collision Warning assessment, and real-time object detection validation. High-fidelity tools Hexagon VTD & ROD, and MATLAB Roadrunner are employed to generate photorealistic, India-specific scenarios capable of modelling detailed road geometry, marked and unmarked lanes, mixed traffic behavior, and diverse environmental and weather conditions. Scenario-driven testing enables frame-accurate, end-to-end assessment of detection, decision-making, and actuation without requiring access to internal algorithms (black-box validation). Across representative scenarios, the test campaign achieved up to 90% accuracy in detecting relevant targets. This validation aligns with AIS & MoRTH guidance, and adheres to UN Regulation (UN R131), while incorporating applicable ISO 26262 functional safety principles. Requirement traceability matrices are used to evaluate system behavior under sensor degradation, misclassification, and other critical edge-case conditions prevalent in Indian driving environments. The proposed methodology enables consistent, repeatable, and regulation aligned validation of camera based AEB systems, supporting safer and more reliable commercial vehicle deployment in India.
S., Nagabhushana N., P., Gururaaj, M. L., Sankar
Children dying in hot cars is not a new problem. Since 1998, more than 1,000 children have died this way in the United States alone — roughly 37 every year. That number has barely been reduced, which tells something alarming: the solutions built so far aren't solving it completely. Door-based reminders are a good example of why. They trigger when a rear door opens, but opening a door doesn't confirm a child was left behind. Single-sensor setups have their own gaps too; no single sensor handles every real-world scenario reliably on its own. Multi-sensor systems get closer, but most use rigid threshold-based rules that fall apart the moment conditions deviate — a sleeping infant barely moves, a child under a blanket reads completely differently on a thermal sensor. This paper proposes Smart-ROPS (Smart Rear Occupant Protection System), an embedded ML architecture that targets these specific failure modes without needing expensive hardware or complex software. Four sensor types feed the system: millimeter-wave radar, CO₂, thermal infrared, and ultrasonic. Data from these passes through three layers — the Perception Layer handles initial sensor fusion, the Processing Layer runs a decision tree as the primary classifier, and when confidence is low, a shallow neural network steps in for ambiguous cases. If a risk is confirmed, the Intervention Layer manages the response: starting with a smartphone alert and cabin ventilation, escalating to emergency services if needed. This is presented as an architectural design contribution — hardware prototyping and real-world testing are left for future work.
Shrimal, Harsh
Overtaking another vehicle on a two-lane road can turn dangerous within a few seconds, especially when the gap to an oncoming vehicle is short or that vehicle is moving fast. Many driver-assistance systems rely on a simple, fast rule called the Overtake Safety Margin formula to decide whether an overtaking maneuver is safe, without running a full traffic simulation. This study checks the formula's reliability using a physics-based simulator that models three vehicles: the car overtaking, the car being overtaken, and the oncoming car. One million generated overtaking scenarios were evaluated using both the OSM formula and the kinematic simulator to identify cases where the formula classified a maneuver as SAFE while the simulator predicted an UNSAFE outcome. These mismatches, called blind spots, represented 3.98% of the evaluated scenarios and were concentrated in high oncoming-speed, short-gap situations, pointing to a specific weakness rather than random error. To catch these blind spots automatically, a small and efficient machine-learning model, a micro-transformer, was trained on the simulator's results. It reached 96.3% overall accuracy and correctly flagged 86.9% of the formula's blind spots, outperforming LightGBM, which detected 73.2%. The model's confidence scores were well calibrated, so they can be trusted to trigger an extra safety check when needed. An uncertainty-based search then used these confidence scores to find risky scenarios efficiently: 187 of the 500 most uncertain cases turned out to be unsafe, about 9.4 times more effective than random selection. Finally, the 30 highest-priority cases were replayed in the CARLA driving simulator, and 27 were confirmed to reproduce unsafe outcomes. Together, these results show that pairing a fast rule-based formula with a calibrated learning-based monitor can catch dangerous situations the formula alone would miss, supporting the safety documentation required for automotive safety-of-the-intended-functionality standards.
Sekaran, Nikhil, Sehgal, Vishal
The application of Advanced Driver Assistance Systems (ADAS) in commercial vehicles marks significant challenges in mechanical design and digital validation of externally mounted sensor systems. Blind Spot Assist (BSA), a radar-based ADAS feature, depends on accurate sensor alignment and stable bracket mounting to ensure reliable detection of objects within the vehicle’s blind spots. the exposure to dynamic loading environments, BSA radar brackets must be designed to withstand operational vibrations and also should comply with international automotive standards, including ISO 16750-3 [1, 7], which outlines test procedures of mechanical vibration and shock. This paper describes a digital approach for the development of BSA radar brackets, incorporating system-level design thinking, flexible-body simulation, and vibration analysis. The method is combination of physical behavior with simulation techniques to study bracket behavior for dynamic loads and identifying probable sources of structure resonance and the interaction of the system with neighboring systems or components. A multi-dimensional design process is highlighted, where multiple iterative modeling, cross-functional teams brainstorming, and virtual validation enables the efficient exploring of alternate designs. The framework supports countermeasure studies such as geometry optimization, boundary condition refining, and system decoupling, with digital development. This approach is applicable for a wide range of ADAS sensor mounts challenges faced in heavy-duty vehicles, where the packaging constraints, harsh operating conditions, and NVH (Noise, Vibration, Harshness) requirements must be considered. This paper shows a replicable model for engineering teams to improve sensor stability, reduce physical testing and simulation cycles, and ensure compliance with vibration standards from the design evolved from simulations.
Kenchaplara, Vinay Kumar, Hubballimath, Nandesh, Sadekar, Rahul
Digital issue management is a critical enabler for accelerating vehicle development and improving launch readiness in automotive programs characterized by distributed engineering, multi-site manufacturing, and increasing electrical/electronic and software complexity. Existing practices often rely on disconnected tools, spreadsheets, and informal communication that delay prioritization, ownership assignment, root-cause analysis, and maturity-gate decisions. This paper presents a standards-anchored semantic issue data model that integrates issue information from engineering, production, quality, supplier, and aftermarket systems without replacing existing tools. The model is aligned with VDA Maturity Level Assurance, IATF 16949, AIAG APQP/PPAP, ISO 26262, Automotive SPICE, VDA 6.3, and the 8D problem-solving method. It is formalized through an entity-relationship schema and supported by a reference architecture comprising a knowledge graph, data ingestion protocols, and integration middleware. A deterministic conflict-resolution mechanism reconciles inconsistent metadata from source systems and establishes an auditable single source of truth. The framework is evaluated using published automotive benchmarks and evidence from five anonymized commercial vehicle implementations across different business units and timeframes. The results demonstrate consolidation of fragmented issue repositories, reduction of system interfaces, elimination of paper-based quality workflows, improved digital-thread coverage, and faster retrieval of previous resolution knowledge. These outcomes indicate reduced cross-functional reconciliation effort, improved ownership transparency, stronger maturity-gate evidence, and measurable launch-readiness analytics. The model also supports future integration with cross-enterprise data spaces for multi-tier supplier collaboration. The proposed framework provides a replicable approach for transforming issue management from a reactive process into a strategic capability for faster and more transparent vehicle development.
Swaminathan, Bharathiraj, Choudhary, Runa, J., Anandu
This paper presents a one-dimensional digital twin of a commercial vehicle heating, ventilation, and air-conditioning (HVAC) system, developed in MATLAB and Simulink with Simscape. The model integrates a belt-driven, engine-speed-dependent R134a vapor-compression cycle with a reduced-order cabin thermal network. The refrigeration loop incorporates a positive-displacement compressor, condenser, thermostatic expansion valve, evaporator, and receiver, with the heat exchangers represented using two-phase and moist-air formulations. The cabin model accounts for six surfaces with parallel glazing and opaque thermal paths, solar and long-wave radiation on exterior panels, occupant heat and moisture loads, and speed-dependent external convection, parameterized for validation drive segments. The framework is designed for traceability from component-level state variables to system-level outcomes, enabling staged validation using pressure and temperature signals across the refrigerant loop and cabin temperature response. Validation was performed against controlled climatic chamber data, including a hot-soak period with the air-conditioning off followed by cool-down tests at two steady vehicle speeds. Simulation results were resampled to match measurement timestamps, showing strong agreement with cabin temperature dynamics, with a root mean square error of ~2 °C and correlation of 0.99 in the transient-excluded window. Refrigerant-side pressures and temperatures exhibited segment-dependent accuracy, sufficient for calibration and strategy assessment. Simulation-based screening of cool-down behaviour and refrigerant-loop states provides a reusable framework before repeated vehicle testing, reducing the calibration effort for faster HVAC system evaluation. Overall, the model supports rapid iteration, ensures thermodynamic consistency through enthalpy-based checks, and provides a practical foundation for controller development and future in-the-loop applications.
Kumar, Nitesh, Duraiswamy, Vijayaraj, M. L., Sankar, Kumar, Vijay Bhooshan
Rollover stability is a critical safety requirement for heavy-duty trucks, particularly during severe manoeuvres and tipping-prone operating conditions. Accurate estimation of stabilizer bar forces plays an important role in assessing vehicle rollover behaviour. This study presents a finite element-based virtual strain gauge calibration methodology for estimating stabilizer bar forces from measured strain signals, using a heavy-duty vehicle tipping stability application as an industrial case study. A high-fidelity vehicle dynamics model was developed to assess the influence of the stabilizer bar on vehicle roll performance. To increase confidence in the virtual assessment, strain measurements were obtained from instrumented stabilizer bars during durability track testing and correlated with simulation results. A key challenge in the measurement process was the calibration required to convert strain signals into applied forces. To address this, a virtual calibration approach was developed using finite element analysis to establish linear strain-force transfer relationships. By combining FEM-derived transfer functions with measured strain data, stabilizer bar forces were successfully reconstructed under real operating conditions without the need for conventional physical calibration. Correlation between simulation and test measurements demonstrated the capability of the proposed methodology to estimate component loads with good accuracy. The results show that virtual strain gauge calibration can significantly reduce reliance on dedicated test rigs and prototype-based calibration activities, enabling earlier load assessment and more efficient chassis development. The methodology is scalable and can be extended to other dynamically loaded suspension and chassis components for durability and vehicle dynamics applications.
Thirunavukkarasu, Siddeshwaran, Sheepri, Sunil, N., Balagangadharan
SAE TOMORROW TODAY - Balancing Innovation and Safety on America's Roads1359211/5/2026
What does it take to make our roads safer while still paving the way for AVs? Listen in as we sit down with Jonathan Morrison, Administrator of the National Highway Traffic Safety Administration (NHTSA), to discuss the agency's approach to roadway safety, AV regulation, and the future of mobility. Want to continue the conversation and hear directly from Jonathan Morrison? Join us at SAE International's Government/Industry Meeting on January 20, 2027, at 12:30 p.m. ET, where he'll moderate a fireside chat with industry leaders on how evolving regulations are shaping product planning, investment decisions, and vehicle affordability. Register now and secure a separate ticket for the lunch and fireside chat. From modernizing outdated regulations to advancing crash test technology, you'll learn how NHTSA is balancing innovation with accountability. The conversation also explores how the A2SCEND Consortium is helping establish safety standards for autonomous vehicles to support their commercialization and build public trust. Beyond autonomous driving, Morrison discusses efforts to reduce traffic fatalities by addressing distracted driving, impaired driving, and seatbelt use. He also examines how updated fuel economy standards could improve vehicle affordability and how next-generation crash test dummies could improve occupant protection. 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 with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.
Patterson, Lori
In assessing lumbar spine injuries of civil aircraft occupants under vertical impact, existing anthropomorphic test devices cannot accurately capture the injury mechanisms. Digital human body models, such as THUMS, are primarily developed for automotive crashes, and their default seated posture differs from that of real civil aircraft occupants. Although the THUMS model can be adjusted to better represent civil aircraft occupants’ seating posture, the mechanical response of the lumbar spine after adjustment has not been sufficiently validated. This limits the model’s reliable use in assessing lumbar spine injuries of civil aircraft occupants. To address this limitation, the THUMS lumbar spine model was modified to reflect aircraft seating posture and physiological lumbar lordosis, and the stiffness of key lumbar ligaments was systematically optimized. Following optimization, the model’s mechanical response curves under flexion, anterior shear, tension, and compression all fell within the post-mortem human subject (PMHS) response corridors, with deviations from the mean PMHS curves significantly reduced. Under the typical 14 g vertical impact specified by FAR 25.562, the optimized lumbar spine exhibited lower peak flexion moments at all lumbar levels, while the axial compressive load and predicted injury risk became more concentrated in the upper lumbar spine. These findings indicate that directly using the original THUMS model may underestimate injury risk in the upper lumbar region while overestimating it in the lower lumbar segments. Posture adjustment, lumbar curvature correction, and ligament stiffness optimization enhance model biofidelity, providing a more reliable basis for the assessment of occupant lumbar injuries.
Shi, Xiaopeng, Jiang, Zihao
Autonomous operations near space targets that do not cooperate present great challenges because position and attitude planning must be linked. A target of this type lacks navigation aids or communication systems, which makes relative motion planning much more difficult. Although methods based on convex optimization work well for problems with three degrees of freedom, like planetary landing, their use in integrated operations with six degrees of freedom is limited by constraints that are not convex. To solve this problem, this paper proposes a new framework for servicing spacecraft using sequential convex programming. The primary contribution is the extension of convex methods to high dimensional trajectory planning while adding a robust trust region constraint based on trajectory deviation. This mechanism reduces the chance of finding no solution during convex approximations. It improves reliability and convergence when solving complex problems. The approach first creates a continuous optimal control problem with an index that balances energy use and the angle of the line of sight. Nonlinear dynamics are simplified using first order Taylor expansions. Constraints for the field of view and collision avoidance are modeled using spherical and ellipsoidal regions. The non convex problem is changed into a sequence of discrete convex subproblems and solved through iterations. Numerical simulations show that the servicing spacecraft can safely approach the target with stable attitude while meeting all physical limits. The method using sequential convex programming with a trust region demonstrates great potential in optimizing computational efficiency alongside strong numerical stability, laying a solid foundation for future real-time autonomous trajectory generation in complex orbital environments.
Wang, Yuzhi, Yao, Zihao, Wang, Qian, Han, Ziwen, Zhang, Chao, Zhang, Yumei, Li, Shunli
The geometric structure of a gas bag has a profound effect on its effectiveness in transferring energy and reliability of its structure when rapidly expanding. Even though there have been considerable improvements in high-performance composite materials such as Kevlar, the transient dynamic reaction and possible rupture mechanisms associated with particular polygon shapes have been greatly unexplored. In this paper, we focus on conventional polygonal gas bags, and perform extensive inflation tests using high-accuracy transient data recorders to monitor the development of the dynamic pressure. In order to overcome the limitations of physical testing, a highly non-linear dynamic finite element model - based upon the application of the *MAT_FABRIC material model in LS-DYNA - is used. This technique allows the systematic examination of how changes in geometric parameters affect the performance of payload dispersion and membrane stress distribution. The results indicate unique ways of deploying depending on their geometry. The circular gas bags are capable of obtaining a velocity of the payload of 4.23 m/s but have high stress concentrations of up to 426 MPa due to the lack of geometric boundaries which make them prone to tearing failure. Rectangular gas bags with very large aspect ratios will experience a tubular expansion deformation that causes energy transfer efficiency to plummet; the release speed of these types of gas bags falls below 2.77 m/s. Ultimately, the optimal structural design is a regular hexagonal shape that optimally balances work performance and structural safety. It can keep good levels of energy transfer efficiency with a final release velocity of 4.12 m/s. Moreover, it successfully stops the continuous hoop tension and reduces the peak stress by around 46 percent through straight edge boundary constraints. This complete research offers an adequate scientific foundation to the anti-burst design of sophisticated polygonal gas bags.
Wang, Jinwei, Shi, Lv, Hou, Jingjing, Li, Yilong, Li, Dailin, Liu, Zhiyi
Detecting surface defects on aircraft is critical to safety in the aerospace field. The current detection methods suffer from low efficiency, high false positive rate and poor adaptability to complex environment. Although the existing target detection algorithms have achieved notable performance in this field, at present, many models in this field still face considerable challenges. For example, due to the constraints of hardware platforms, machines that can be deployed on edge devices such as UAVs and robots need lightweight and easy-to-deploy models, but lightweight designs often a certain degree of accuracy degradation. At the same time, most of the surface defects of the aircraft are small targets, which impose higher demands on the model. In order to solve these limitations, this paper proposes an improved YOLO model ME-YOLO (multi directional edge fusion YOLO) based on edge enhancement and multi-scale fusion. Firstly, the EdgePyramid module is designed, which uses the rich edge responses extracted by the Multi Orientation Attention Sobel (MOAS) module and through the three-layer cascade pool structure to construct the three-scale edge features aligned with the backbone network. Then, the EdgeEnhance module is introduced to adaptively fuse the conventional convolution features and edge features at the corresponding resolution, effectively enhancing the sensitivity of the model to the corrosion boundary. Experimental results show that, compared with the baseline YOLOv11, ME-YOLO improves mAP@0.5 by 2.7% and simultaneously increases Recall by 2.3%, which helps reduce missed detections of corrosion targets. Although the introduction of multi-directional edge priors brings a slight increase in parameters (+3.66M) and a minor decrease in inference speed (--8.6%), the model still maintains a real-time detection capability of 97.54 FPS, meeting the deployment requirements for edge devices such as UAVs. This strategy of trading a modest computational overhead for improved detection rates in safety-critical tasks offers a potentially practical and robust alternative for intelligent operation and maintenance of aviation equipment.
Zhou, Xing, Li, Yuan
In order to meet the airworthiness regulations, the civil aircraft propulsion system needs to carry out the necessary fireproof test. The measurement of the flame temperature is very essential for the certification and validation of fire protection thermal simulation models, and also helps to establish the empirical understanding of complex flame behaviors. In order to investigate the influence of the specimen on the flame temperature distribution, the two dimensional flame temperature distribution of the free burning test and several fireproof tests, including titanium panel fireproof tests, stainless steel panel fireproof tests, composite laminated panel fireproof tests, honeycomb sandwich panel fireproof tests, were experimental investigated in this paper. The test results shows that panel specimens significantly alter the temperature distribution of the standard flame and interfere with radiation heat transfer measured by thermocouple, resulting in a significant reduction in the temperature gradient of the flame and a obvious increment in the temperature of the surrounding non-flame-impinging zone. The central flame-impinging zone exhibits minimal temperature variation compared to the baseline flame at 1093 °C, with temperature elevation restricted to approximately 40 °C (within 4% deviation). Both metal panels and composite panels demonstrate consistent trends in affecting flame temperature distribution. However, compared to metal panels, composite materials induce smaller temperature gradients and more uniform temperature fields. Multiple burning tests on same panel progressively intensify the oxidation on the specimen surface, leading to a gradual decrement in flame temperature. Especially, this temperature reduction becomes statistically significant as early as the second time burning test.
Chen, Fang, Guo, Junxian, Peng, Sen
With the increasingly widespread application of airborne software in civil aircraft and the continuous growth of its functional complexity, the frequency of software modifications has risen significantly. The traditional factory-return loading mode leads to high operating costs and long maintenance cycles. Focusing on the design of field-loadable software for civil aircraft, this paper proposes a decision-making strategy for determining whether airborne software should be designed as field-loadable software. This strategy classifies airborne software into three categories, platform basic software, functional software, and database software. It puts forward the design principle that field-loadable design is mandatory for database software, preferred for functional software, and not mandatory for platform basic software. In addition, a multi-dimensional design deviation assessment model is constructed for software that cannot meet the above requirements. Functional software that is not designed as field-loadable and has not yet been installed on aircraft shall be evaluated from five dimensions: interconnection complexity, software characteristics, airline operation, commercial off-the-shelf (COTS) attributes, and competitor aircraft models. For functional software that is not designed as field-loadable but has already been installed on aircraft, three additional evaluation dimensions shall be included: the possibility of software modification, difficulty of optimization, and cost of optimization. Meanwhile, this paper analyses the airworthiness requirements to be considered in the design of field-loadable software, as well as the design considerations required to address problems arising in the delivery process, such as configuration identification Issue, granularity issue of field-loadable software packages and format issue of field-loadable software packages. The research provides a systematic reference for the design decision-making, airworthiness compliance and efficient delivery of civil aircraft field-loadable software, helping to shorten aircraft downtime and reduce airline operation costs.
Feng, Chen, Fan, Hui, Luo, Jialu
Aerospace search and rescue plays a crucial role in ensuring the safety of manned space missions. As China’s manned space program progresses toward normalization and higher-frequency, flight-like missions, the conventional static formation mode of search and rescue forces may no longer be adequate. To achieve the “high frequency, high parallelism, and multi-type” goals in future missions, we propose a more efficient contract net algorithm that incorporates hierarchical bidding and joint evaluation to dynamically organize and optimize distributed tasks. The force formation challenge is modeled as a distributed dynamic programming problem with strong spatiotemporal constraints, and a task-capability-context matching is developed to overcome the adaptability limitations of static formation modes in flight-type missions. To enhance the contract net, we introduce a Level 1 bidding algorithm based on efficacy objectives, which builds a “timeliness-loss-reliability” objective function using these three indicators. Then, we introduce a Level 2 bidding algorithm focused on equilibrium objectives by employing “rigid locking for high-priority tasks and dynamic optimization for secondary tasks” to alleviate resource load imbalance. Next, we implement a ”joint bidding” mechanism, which allows resources to form alliances and bid collaboratively. Simulation results demonstrate that the improved algorithm accelerates task formation and provides a systematic, scientific solution for aerospace search and recovery force formation.
Lv, Nan, Liu, Ruirui, Li, Donghao, Liu, Xin
2025–2026 Reviewers
Hardy, Warren
The widespread use of explosive weapons in recent military conflicts has contributed to an increased incidence of traumatic brain injuries. Although current infantry helmets provide effective protection against fragmentation, ballistic impact, and blunt trauma, they are not designed to mitigate primary blast loading. Previous studies suggest that blast waves may infiltrate the space between the head and helmet, leading to localized increases in pressure on the head surface, a phenomenon referred to as the underwash effect. However, experimental validation of the underwash effect remains limited, particularly for blast scenarios representative of buried-charge detonations, despite their potential to increase underwash-related loading across large regions of the cranial surface. This study experimentally evaluated the effects of combat helmet use, blast orientation, and blast intensity on head surface loading to assess helmet protective performance across various blast scenarios. A human surrogate headform instrumented with four flush-mounted pressure sensors was exposed to blast overpressures of approximately 16 and 24 psi using a large advanced blast simulator. Tests were conducted at 0° and 45° head orientations (rotation about the transverse axis), both with and without a combat helmet, with three repetitions per combination of experimental conditions. In the 0° orientation, helmet use reduced loading at the forehead and anterior head but increased loading at the posterior region. In the 45° orientation, helmet use led to increased peak pressure and total impulse at all measured locations. Increasing the blast intensity resulted in similar trends for both orientations and helmet conditions but with greater peak pressures and total impulses at each measured location. These findings suggest that certain blast orientations exacerbate the underwash effect and amplify cranial loading beneath the helmet. This work advances understanding of orientation-dependent blast loading, highlights limitations in current helmet performance, and offers guidance to support the development of future protective technologies.
Nelson, Allison J., Burt, Ethan T., Hamilton, Joseph M., Espinoza, Kenny J., Magallanes, Joseph, VandeVord, Pamela J.
Globally, approximately 11 million pedestrian impacts each year result in injury or death. The lower extremity is the most frequently injured body region in pedestrian impacts, and these injuries often lead to long-term disability. To better understand lower-extremity injury risk, biomechanical testing of the leg and tibia has previously been conducted. However, this work has mainly focused on males, despite females having a higher risk of sustaining lower-extremity injuries in these loading events. This study aimed to evaluate the effects of sex and age on biomechanical properties of the isolated human tibia in a diverse sample. Sixty-six tibiae from 35 females and 31 males with similar age distributions (p > 0.05; females = 68.8 ± 3.4 years; males = 59.8 ± 4.0 years) were utilized. Tibial diaphyses were loaded to failure at 6 m/s in lateral–medial four-point bending to replicate vehicle bumper interaction in pedestrian impacts. Reaction forces were measured at each end of the bone. Proximal and distal moments were calculated as the product of reaction force and the distance from the axis of rotation to the nearest impact site. Peak bending moment at midshaft was further calculated as the maximum of the average proximal and distal moments. Strain at time of fracture was determined from axial strain gages on the lateral and medial bone surface between impactor locations. Maximum deflection was normalized by specimen length and area moment of inertia. Males exhibited significantly greater peak moments than females (p = 0.001). In the full sample, age demonstrated a weak but significant negative relationship with peak moment (p = 0.013, R2 = 9.3%); however, no significant age relationship was observed when males or females were analyzed separately. Male tibiae had a significantly greater deflection than female tibiae (p = 0.001), but no significant sex difference was observed with normalized deflection. Age was strongly and negatively associated with deflection in the full sample (p < 0.0001, R2 = 39.7%), and for males (p < 0.0001, R2 = 44.8%) and females (p < 0.0001, R2 = 25.4%) separately. No significant sex differences were observed for tensile strain at fracture. However, age had a significant negative relationship with tensile strain in the full sample and within each sex (p < 0.0001). Further investigation with larger sample sizes is needed to characterize the interacting effects of sex, age, and size. Overall, this work advances understanding of tibial biomechanics and provides insight for improving pedestrian safety tools including anthropomorphic test devices and human body models.
Spangler, Jonathon, Agnew, Amanda, Kang, Yun-Seok, Kemper, Andrew, Hunter, Randee, Baker, Gretchen, Guettler, Allison, Harden, Angela
The performance of Midwest Guardrail Systems (MGS) during impact with electric vehicles (EVs) has raised concerns with recent observations demonstrating a higher susceptibility to rail failures. These failures are hypothesized to be related to EV-specific design, including variations in front-end geometry and inertial properties. Current guardrail evaluations rely on two vehicle types, a small car and a pickup truck, potentially overlooking sensitivity to front-end geometry variations, potentially leading to unanticipated impact responses. Additionally, the extent to which geometry influences occupant injury risks and trends during vehicle-guardrail impact remains insufficiently investigated. The objective of this study is to quantify the influence of vehicle front-end geometry on occupant injury risk during vehicle-guardrail impacts using finite element (FE) simulations. Occupant injury risk is analyzed using Hybrid III anthropomorphic test device (ATD)-based injury criteria and flail space-based vehicle severity metrics to identify trends and relationship between geometric variations and injury probability. Front-end geometry data from the Insurance Institute of Highway Safety (IIHS) were analyzed to identify parameters and ranges associated with adverse MGS performance. Based on vehicle alignment with the W-beam, hood leading-edge height, hood leading-edge angle, and bumper height were morphed on the Toyota Yaris model. A Latin Hypercube Design of Experiments generated 13 unique configurations for detailed analysis. Full-scale Manual for Assessing Safety Hardware (MASH) Test Level 3 FE simulations were then performed between the morphed vehicle models integrated with Hybrid III 50th percentile male ATD and MGS guardrail. Occupant injury metrics were evaluated alongside vehicle-based crash severity measures. All vehicle geometries fulfilled MASH criteria with occupant impact velocity (OIV) and occupant ride down acceleration (ORA) within tolerance with no rail rupture. Simulations suggest that probability of serious full-body injury (AIS3+) was estimated at 17.11% while probability of severe neck injury was the highest at 15.64% among the component level probabilities. While front-end geometry influences occupant kinematics, resulting injury metrics and vehicle-guardrail interaction characteristics, it does not independently govern occupant injury risk. Although, the MASH tests have the same outcome as the geometries studied, the changes in EV inertial properties could interact with the geometry leading to barrier failure, which will be explored in future work.
Bubna, Maheep, Buckland, Elijah, Riexinger, Luke E., Untaroiu, Costin
Pelvis fractures can be complex and occur in many different regions of the bone. Loading due to side impact can transfer anteriorly through the pubic symphysis and posteriorly through the sacroiliac joint. Virtual testing with human body models (HBMs) has the potential to capture the complex loading mechanisms that contribute to pelvis fractures, but injury prediction with HBMs must be refined and validated using physical test data. Most postmortem human subject (PMHS) studies testing side-impact and pelvic injuries use simplified test modes rather than simulating realistic boundary conditions. It is important to understand the differences between pelvis fractures resulting from in-lab tests and those sustained in real-world collisions, particularly for when these PMHS tests are used in injury risk function development to predict injuries caused by collisions in the real world. This study seeks to compare injury types and loading mechanisms from existing PMHS tests to those observed in real-world side-impact collisions from Crash Injury Research and Engineering Network (CIREN) to examine their suitability for refining HBM injury prediction for the pelvis. Seventy-seven percent of PMHS tests with injuries had fractures in the anterior region of the pelvis, 23% in the iliac wing, 30% in the sacroiliac region, and 16% in the acetabulum, where a PMHS test could have fractures in multiple regions. Fractures were divided into primary- and secondary-side fractures, where the primary side was defined as the side impacted in a PMHS test and the side closest to the crash in a CIREN case. A higher proportion of cases with secondary-side acetabulum and sacroiliac pelvis fractures was observed in CIREN compared to PMHS tests, which may be related to interaction with structures in a vehicle environment. A pattern of “squeezing” the pelvis between the intruding door and the center console in near-side crashes was observed.
Nazari, Isabella, Heo, Jaehyuk, Gepner, Bronislaw, Forman, Jason
Lower extremity injuries remain common in frontal motor vehicle crashes, with evidence suggesting increased vulnerability among female occupants. While prior research has established failure tolerances of midsize male lower extremities under bending and combined loading conditions, limited data exist for small female specimens. This study aimed to characterize and compare the failure tolerance of small female and midsize male postmortem human subject lower leg specimens under combined axial compression and posterior–anterior (PA) bending using consistent boundary conditions. Twenty-four lower leg specimens, including the tibia, fibula, and surrounding soft tissue, were obtained from 50th percentile male (n = 12) and 5th percentile female (n = 12) donors. Dynamic tests to failure were conducted at 1.5 m/s using a test apparatus designed to apply three-point bending in the PA direction with varying levels of superimposed axial compression (0, 2, 4, and 6 kN). When paired left and right legs from the same donor were available, they were assigned to different loading conditions to assess the influence of axial compression magnitude. Fracture timing was determined using force, strain, acoustic emission data, high-speed video, and post-test CT imaging. Results indicated that 18 specimens fractured at the tibial shaft, 5 near the potting interface, and 1 did not fracture. Under pure bending, mean failure moments were 255 ± 57 Nm for males and 156 ± 15 Nm for females. At 6 kN axial compression, failure moments decreased to 195 Nm and 72 Nm for male and female specimens, respectively. Among matched pairs, increasing axial load resulted in an average 21% reduction in bending moment at failure. These findings demonstrate reduced failure tolerance with increasing axial compression and highlight sex-based differences. The data provide a foundation for developing improved injury risk functions and scaling methodologies for diverse occupant populations as well as informing anthropometric test devices and human body models.
Carbon, Maria, Nazari, Isabella, Edinger, Timothy, Shin, Jeesoo, Hanggi, Connor, Kerrigan, Jason, Forman, Jason
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.
Jung, Caitlyn, Stark, Nicole E.-P., Rowson, Steve
Fifteen research posters were prepared and presented by student authors. The posters covered a wide breadth of works-in-progress and recently completed projects. Topics included a variety of body regions and injury scenarios: Assessment of Layered Seat Cushion Configurations for Underbody Blast Protection Quantifying Head Impact Exposure in Collegiate 15s Rugby and Relationship to Clinical Measures Elderly Fatality in CIREN Cases: A Matched-Case Review The Relationship between Injury Risk for Child, Teen, and Adult Pedestrians in Collisions Preceded by PAEB Activation and PAEB Pulse Characteristics Quantifying Kinematic and Vibrational Responses in Hockey-Style Catcher’s Mask Incorporating Cortical Bone Property Variability into Simulations of Isolated Ribs under Anterior–Posterior Bending Lacrosse Ball Impacts on Women’s Headgear Mechanical Characterization of the Liver and Kidney: A Systematic Review Quantifying Changes in Mouthguard–Dentition Fit to Support Head Impact Measurement Validity Whole-Body MRI to Assess Perfusion Success and Soft Tissue Injuries in PMHS Subjected to High-Rate Loading Quantitative CT and MRI-Based Modeling Assessment of Spine Injury Risk Following Long-Duration Spaceflight An Investigation of Local Accelerator Pedal Geometry Effects on Ankle Motion How Do Different Human Body Models Affect Occupant Impact Responses and Restraint Design Optimizations in Frontal Crashes? The Potential Effects of Youth Hockey Helmet Shell Add-Ons Evaluation of Surrogate Soft Tissue Candidates for Biofidelity and Durability
Forman, Jason, Mueller, Becky
Instrumented mouthguards (iMGs) capture thousands of head acceleration events in contact sports, though processing the data from these into meaningful information remains a challenge. To bridge this gap, we developed a principled clustering pipeline to extract concise kinematics that are representative of real-world impact scenarios. We evaluated six multivariate time-series distance metrics using k-medoids clustering and a dataset of 5149 impacts across three sports: mixed martial arts, boxing, and rugby union. Model performance was evaluated using a Coverage Quality Score (CQS), prioritizing reconstruction coverage and cluster separation. Joint Shape-Based Distance (SBD) significantly outperformed all other metrics, including Dynamic Time Warping (DTW), driven primarily by superior reconstruction coverage. The methodology yielded two complementary archetypes. First, a 36-impact canonical set provides distinct medoids representing core kinematic mechanisms; however, distributional checks confirm these medoids alone do not reproduce cohort severity distributions. To resolve this, we generated a second, extended impact set sampled proportionally within clusters along specific severity axes (e.g., peak acceleration and whole-brain strain). This targeted sampling recovers full severity-distribution fidelity using fewer than 150 impacts per dataset. Ultimately, this framework successfully distills large iMG datasets into manageable cohorts providing a scalable solution for assessment, experimental targets, and finite element simulations.
Koumantou, Eleni, Chan, Emily Yik Kwan, Jones, Chris M., Austin, Kieran, Loosemore, Mike, Ghajari, Mazdak
Pilon fractures are a severe lower-extremity injury sustained in motor vehicle crashes, characterized by high-axial loading that drives the talus into the tibial plafond and frequently results in poor long-term functional outcomes and post-traumatic osteoarthritis (PTOA). Despite advances in surgical management, clinical complications remain frequent in 20–50% of cases in literature, which highlights the need to identify modifiable upstream risk factors in the motor vehicle crash environment. The Abbreviated Injury Scale (AIS) is the predominant tool for crash injury severity analysis, and it classifies all closed pilon fractures uniformly as moderate (AIS 2) regardless of comminution or imparted energy and poorly predicts long-term functional outcomes. An existing fracture energy severity metric quantifies the acute mechanical energy delivered to bone during fracture and has been linked to PTOA development. This study represents one of the first multivariate applications of the fracture energy metric to crash data, examining how occupant demographics, crash kinematics, and vehicle safety systems relate to pilon fracture severity. Fifty belted occupants with Orthopaedic Trauma Association (OTA) Type B or Type C pilon fractures were identified through the Crash Injury Research and Engineering Network (CIREN) database. Fracture fragment surface models were generated from clinical computed tomography (CT) and used to compute fracture energy severity through a custom MATLAB script. A generalized linear model with a gamma log link was fit using seven predictors: age, delta-v, knee bolster airbag (KBAB) deployment, fracture loading mechanism, biological sex, osteoporosis, and body mass index (BMI). KBAB deployment and pure axial compression loading were both significantly associated with higher fracture energy (p = 0.011 and p = 0.002), and age approached an inverse association (p = 0.086). These findings establish the fracture energy metric as a viable tool for crash injury analysis and suggest that certain vehicle safety system characteristics warrant further investigation as modifiable factors influencing pilon fracture severity.
Northrup, Samuel, Bangert, L. Garrett, Armstrong, William, Stitzel, Joel D., Martin, R. Shayn, Dibbern, Kevin, Anderson, Donald D., Weaver, Ashley A., Collins, Caitlyn J.
Biomechanical response targets for the thorax have largely focused on the 50th percentile male, limiting their relevance for smaller females. Previous studies have provided side-impact female postmortem human subjects (PMHS) data from either oversimplified or realistic boundary conditions. This study aimed to generate thoracic biomechanical responses of small female PMHS in a simplified side-impact condition with realistic components and compare responses between two input energy levels. Twelve small female PMHS were seated on a simplified seat with FMVSS No. 213a seat foam and fabric and impacted once on the left thorax with either a 14.0 kg (low energy) or 23.7 kg (high energy) pneumatic impactor at 4.5 m/s. A rectangular impactor face (22.9 × 25.4 cm) covered with FMVSS No. 213a armrest foam simulated an intruding door panel. Thoracic deflection was measured using a chestband. Inertially compensated force was recorded via a load cell. Spinal kinematics were captured using six-degree-of-freedom motion blocks. Biomechanical responses were compared between groups using two-sample t-tests. The high-energy group exhibited significantly higher peak forces (2.5 vs. 1.9 kN, p = 0.0001), greater thoracic deflections (41.0 vs. 33.9 mm, p = 0.016), and increased deformation energy (91.6 vs. 61.0 J, p = 0.0001). Effective stiffness did not differ significantly between groups (p = 0.734). Energy loss increased with impact severity (66.2 vs. 56.7%, p = 0.020). Kinematic responses also increased with increased input energy. Peak y-accelerations were significantly greater at T4 in the high-energy group (p = 0.049). The sternum exhibited significantly greater peak z-angular velocity in the high-energy group (p = 0.038). Mean BioRank System Score (BRSS) of the force–deflection corridors between groups was 0.93. In summary, these findings provide essential biomechanical data and establish an important foundation for developing improved testing conditions and advancing the evaluation of female human body models (HBMs) and anthropomorphic test devices (ATDs) in side-impact scenarios.
Anantharamakrishnan, Srinivas, Kemper, Andrew, Baker, Gretchen H., Guettler, Allison J., Rhule, Heather, Kang, Yun-Seok, Agnew, Amanda M.
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.
Pang, Derek Y., Salzar, Rober S., Boggess, Brian M., Bass, Cameron R.
Robust restraint system design requires effectiveness across varied anthropometries. Biofidelity reference datasets of postmortem human surrogates (PMHS), a necessary component of informing and assessing restraint system design, exist for the midsize males and small females, but there is limited research for other anthropometries such as the midsize female and obese populations. The goal of this study was to evaluate the kinematic and injury response of midsize female, elderly midsize female, obese female, and obese male PMHS in upright frontal impacts in a simplified restraint environment. The test condition in this study was a full-frontal 30 km/h impact. The test fixture consisted of a rigid seat, knee bolster, footpan, a custom 3 kN shoulder belt force limiter, and separate shoulder and lap belts. Twelve tests were performed with PMHS of varied anthropometries: three per occupant type (midsize female, elderly midsize female, obese female, and obese male). The restraint environment limited the movement of the lower extremities, isolating the thoracic response. Shoulder belt lengths and positioning varied by occupant type. Peak shoulder belt force values ranged between 2.8 and 4.4 kN. Differences in soft tissue distribution (including the hips, abdomen, and breasts) affected both the pre-test path of the shoulder belt on the thorax and the belt’s subsequent motion relative to the thorax during the test. Rib fractures were observed across all four occupant types ranging from 0 to 19 fractures. Occupant anthropometry affected the impact and injury response of the PMHS in this study, demonstrating the breadth of the population over which restraint system robustness is required.
Gallaher, Mary K., Donlon, John-Paul, Nazari, Isabella L., Mann, Logan M., Hollar, Reagan T., Sochor, Sara H., Noss, Junior R., Forman, Jason L.
Letter from the Guest Editors
Mueller, Becky, Forman, Jason
The guiding hypothesis for this project is that wheelchairs compliant with RESNA WC19 voluntary standards for vehicle crashworthiness could meet aircraft seating crashworthiness standards specified by the FAA. This article documents methods and results of static testing. Companion efforts for dynamic horizontal and vertical dynamic testing are reported elsewhere [1]. Surrogate 4-point-strap tiedowns secured the wheelchairs in all tests, using the geometry specified for WC19 testing. Nine different commercial wheelchairs, representing a range of designs, were tested using adapted versions of FAA procedures for static loading in five directions. Occupant restraint conditions included both a wheelchair-anchored lap belt and a floor-mounted lap belt. Tested wheelchairs met static requirements for integrity and deformation, despite multiple tests conducted on the same wheelchair. These results support future use of personal wheelchairs as seating on aircraft, provided the wheelchairs meet WC19 requirements. Additionally, the wheelchairs must be secured with 4-point-strap tiedowns, and occupants should be restrained using both a wheelchair-mounted belt and a supplemental lap belt anchored to the aircraft.
Orton, Nichole R., Manary, Miriam A., Vallier, Tyler, Boyle, Kyle J., Klinich, Kathleen D.
The high-stability bracket is the primary component in remote sensing satellites responsible for carrying the camera and attitude control equipment; its dynamic behavior directly affects imaging quality and in-orbit service life. Welding-based connections introduce uncertainties during manufacturing and assembly, leading to significant discrepancies between finite element analysis results and experimental data. To quantitatively assess the impact of welding processes on the accuracy of the high-stability bracket’s finite element model(FEM), this study proposes a Bayesian parameter correction method based on Markov Chain Monte Carlo (MCMC) sampling and the Metropolis-Hastings (MH) algorithm. It employs a multilevel correction experimental framework—”material-level, component-level, and system-level”—to progressively refine material parameters and establish a high-fidelity FEM. First, the elastic modulus of the welded and non-welded regions were calculated using stress-strain curves obtained from static tensile tests on welded and non-welded plates; then, targeting the first two natural frequencies from dynamic impact tests on bar specimens, the material densities of the welded and non-welded regions were corrected using the Bayesian method; finally, the effectiveness of the correction method was verified through free vibration tests on the actual high-stability bracket. The results indicate that, compared to the undamaged region, the welded region exhibits a 13.87% loss in elastic modulus and a 55.32% loss in density. The relative errors in the first three natural frequencies of the corrected model were 0.59%, 0.01%, and 0.83%, respectively, verifying the high reliability of the proposed method in modal identification and providing a new technical approach for correcting spacecraft structural models.
Liu, Kun, Guo, Chongchong, Wu, Wenhua
Fractal antennas have attracted considerable attention due to their compact geometry and favorable electromagnetic characteristics, particularly in broadband and multiband applications. In this paper, a fourth-order Hilbert fractal antenna is designed and analyzed for radio frequency signal reception in the 200-300 MHz band. The design is motivated by the spectral characteristics of electromagnetic radiation generated during corona discharge, whose primary energy is concentrated within this frequency range. The proposed antenna is optimized in terms of return loss and bandwidth to ensure effective signal reception. Simulation results demonstrate that the antenna exhibits satisfactory impedance matching and achieves stable performance within the target frequency band. Based on the optimized design, a prototype is implemented and evaluated through laboratory experiments. Experimental results indicate that the proposed antenna can effectively capture radio frequency signals associated with corona discharge, demonstrating reliable non-contact detection capability. The study provides a feasible antenna design approach for corona discharge monitoring and offers potential applications in avionics system health management and electromagnetic sensing.
Hei, Guoyu, Li, Shidong, Wu, Yang, Su, Zhenxia, Ye, Hongyan
Geostationary Earth Orbit (GEO) satellites, as a crucial infrastructure for global communication and emergency support systems, are highly valued due to their wide coverage, long communication distances, and large transmission capacity. However, the scarcity of orbital slots and the difficulty in quickly identifying available satellites in actual user scenarios have become the main bottlenecks restricting the communication efficiency of multi-satellite relay systems in geostationary orbit. To address these issues, this paper proposes an accurate and efficient method for selecting the set of available satellites for multi-satellite relay applications. We construct a spatial coverage model based on the H3 hierarchical discrete global grid system and a geometric model that characterizes the visible orbital arc of the user station. By comprehensively considering the geographic locations of gateway stations and user stations, satellite beam coverage boundaries, and the visibility constraints imposed by user terminal antenna pointing, the proposed method can accurately screen out qualified satellite sets that satisfy the end-to-end link condition of “gateway–satellite–user station”. Simulation experiments are conducted in the Ku-band to validate the effectiveness of the proposed scheme, with performance metrics including coverage probability, accessible satellite quantity distribution, and selection efficiency evaluated. The results show that the H3-based modeling approach effectively reduces computational complexity while ensuring high accuracy in visibility judgment. The proposed method significantly improves the accuracy and efficiency of satellite selection, and supports dynamic updates in mobile user scenarios. This work presents a reliable satellite selection algorithm, which can be used to support efficient resource scheduling and provide a strong guarantee for GEO multi-satellite relay communication.
Yu, Xinyue, Jiang, Yanzi, Lu, Yi, Hou, Yucheng, Su, Xingyu, He, Wenxi, Zhang, Jie
This paper focuses on three typical external fire scenarios in aircraft firefighting and rescue training systems: engine fires, external fuselage skin fires, and nose landing gear fires. Unlike internal fires, these external fires expose the load-bearing steel structure directly to flame radiation and high-temperature environments, and the cooling methods and stress conditions associated with each fire scenario differ significantly. Based on the ABAQUS finite element platform, this study established a three-dimensional finite element model comprising an engine model, a water-cooled thermal insulation structure, and a fuselage support system, fully accounting for the actual structural layout and cooling protection measures of the training system. Material parameters were derived from measured performance data for Q355NH steel. The calculation results indicate that under the three types of external fire scenarios, the steel structure model maintained sufficient structural safety margins, with a minimum safety factor of 4.49 and a maximum of 9.43. This demonstrates that the current design meets the safety requirements for prolonged external fire training, providing a reliable mechanical basis for the safe operation of the ARFF training system.
Gao, Jianwei, Xu, Xiaodong, Huang, Min, Wang, Shumin, Shi, Yajie, Zhang, Yun
Aiming at the constraint issues of adjacent spacecraft solar panel collision avoidance and formation keeping in the pose tracking control of spacecraft formation, this paper proposes a distributed relative position and attitude cooperative control strategy on the basis of high-order control barrier functions. First, nominal control strategies for relative position and attitude tracking using the sliding mode control method to achieve high-precision tracking of relative motion are de-signed. Then, high-order control barrier functions suitable for solar panel collision avoidance and spacecraft formation keeping constraints are constructed. The control strategy constraints satisfying safety specifications are derived based on the forward invariant set theory. Finally, a quadratic programming optimization framework is established by combining the nominal control strategies and constraint conditions and then we obtain the optimal control strategy by solving this framework. Numerical simulations verify that the designed control scheme achieves precise tracking of relative position and attitude for spacecraft formation, avoids collisions between solar panels of adjacent spacecraft and prevents excessive loosening of the formation configuration.
Zhu, Ziqi, Qin, Wenyu, Lyu, Yueyong
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