Browse Topic: Crashes

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Impact of Transient Driving Characteristics on Bench-to-Road Emission Consistency of Light-Duty Vehicles2026-99-15739/11/2026
The thalweg at the outlet of the Yuxikou Waterway transitions from right to left, forming a 90-degree bend. It then merges with the Xihua Waterway after passing Xiliang Mountain, creating a main-branch confluence water area. Taking a typical main-branch confluence water area in the lower reaches of the Yangtze River as the research object, this paper reflects the current navigation status and existing problems of ships in the area through the analysis of ship traffic flow. It classifies the risk levels of passing ships, proposes suggestions for route reform and optimization, and uses a model to verify the probability of collision accidents in the area after the implementation of the round-island navigation method, providing a reference for the navigation safety of passing ships.
Qiao, Jiajun, Jin, Zhenhua, Huang, Qi, Li, Guohui, Zhang, Xinguo
ASTDGCN: An Adaptive Spatial-Temporal Diffusion Graph Convolutional Network for Traffic Forecasting2026-99-15839/11/2026
Precise traffic flow prediction functions as the fundamental cornerstone for the efficient, safe, and reliable operation of intelligent transportation systems (ITS). It not only provides data-driven support for key applications, for instance, real-time traffic signal regulation, proactive congestion mitigation, and personalized route optimization, but also exerts a critical effect on reducing traffic accidents and improving overall urban travel efficiency. However, the traffic system belongs to a complex system, with spatio-temporal dynamics that are both intricate and variable, ranging from predictable fluctuations during morning and evening peak hours to localized propagation effects caused by accidents, as well as seasonal variations and significant nonlinear characteristics. These factors collectively pose substantial challenges to building accurate and reliable prediction models, creating a long-standing technical bottleneck in this field. With the aim of solving the dilemma that existing methods are hardly able to capture traffic flow’s spatio-temporal dependence effectively, we advance an adaptive spatial–temporal diffusion graph convolutional network (ASTD-GCN) for a traffic flow prediction model that integrates adaptive graph learning, diffusion convolution, and bi-directional long short-term memory network (Bi-LSTM) with attention mechanism. The model dynamically constructs the correlation between the nodes of the transportation network through the adaptive graph learning module and accurately describes the spatial topology. The diffusion convolution module realizes multi-order spatial information diffusion based on graph structure, which realizes the effective extraction of the traffic flow’s spatial dependence features. The Bi-LSTM module incorporating the attention mechanism captures the historical and future context information of traffic flow simultaneously through the bidirectional loop structure and the temporal attention mechanism, and strengthens the key time step features. Experimental results on -world traffic datasets PEMS03, PEMS04, PEMS07, and PEMS08 indicate that our proposed model exhibits better predictive precision in traffic flow forecasting tasks than baseline counterparts.
Li, Sumin, Gao, Yina, Zhu, Hongnian
Current Situation of Ship Navigation and Research on the Route Reform Scheme in Typical Tributary-Confluence Waters of the Lower Yangtze River2026-99-15729/11/2026
The thalweg at the outlet of the Yuxikou Waterway transitions from right to left, forming a 90-degree bend. It then merges with the Xihua Waterway after passing Xiliang Mountain, creating a main-branch confluence water area. Taking a typical main-branch confluence water area in the lower reaches of the Yangtze River as the research object, this paper reflects the current navigation status and existing problems of ships in the area through the analysis of ship traffic flow. It classifies the risk levels of passing ships, proposes suggestions for route reform and optimization, and uses a model to verify the probability of collision accidents in the area after the implementation of the round-island navigation method, providing a reference for the navigation safety of passing ships.
Liu, Ka, Xu, Yerong
Safety Analysis of Collision Avoidance for Semi-Autonomous Navigation Ship Based on STPA-CREAM2026-99-15549/11/2026
With the continuous improvement of ship intelligence, more intelligent onboard navigation equipment and intelligent navigation systems are used to assist in improving navigation efficiency. This study takes semi-autonomous navigation ships as research objects and adopts System-Theoretic Process Analysis (STPA) to model the complex interaction relationships of semi-autonomous navigation encounter scenarios and identify and analyze potential risks. To address the deficiency of STPA in human factors analysis capability, the Cognitive Reliability and Error Analysis Method (CREAM) is introduced to analyze human factors in semi-autonomous navigation. Finally, based on the results of the STPA-CREAM analysis, recommendations are provided to improve the safety of semi-autonomous navigation.
Zhang, Xiaojie
DisReID: Single Domain Generalizable Person Re-ID Method for Highway Construction & Operation2026-99-15309/11/2026
With the advancement of computer vision technologies and the widespread deployment of video surveillance systems, traffic safety and the development of intelligent highways have been significantly enhanced. As a key component of the intelligent video analysis module in smart highways, person re-identification (re-ID) addresses critical challenges, including cross-segment tracking of pedestrians illegally using emergency lanes, multi-camera joint searches for lost persons in service areas, and trajectory tracing of individuals involved in traffic accidents. These functions directly support the core goals of "safety assurance and efficient service" for smart highways. However, due to the complexity of the application scene, its generalization to unseen environments remains a core challenge. This problem is formally studied under the setting of Single-Domain Generalizable Person Re-identification (SDG re-ID), which aims to train a model on a single source domain that can perform well on arbitrary unseen target domains. To handle this issue, this paper proposes a novel Disentangled Augmentation re-ID Framework (DisReID) that disentangles and augments both structure and style. Specifically, DisReID consists of two modules: Structure-aware Viewpoint Simulation (SVS), a novel pre-processing technique that simulates cross-camera perspective changes by perspective transformation, diversifying geometric structure without harming identity semantics; and Style-Dominant Frequency Perturbation (SFP), which selectively focuses on the style-dominant frequencies and applies perturbation to enable controllable style augmentation while preserving structure cues. Furthermore, to alleviate the BN-induced domain bias, we introduce a simple yet effective test-time adaptation strategy, termed Cluster Fine-tuning (CF), that performs unsupervised clustering on target-domain features to assign pseudo-labels and subsequently fine-tunes the model, enhancing adaptability to unseen domains. Extensive experimental results on four public datasets demonstrate that our DisReID achieves superior generalization performance compared to the state-of-the-art methods. This work provides key technical support for the large-scale application of re-ID in smart highways, advancing the goal of "full-domain perception and intelligent collaboration".
Pan, Hong, Yu, Fangying
Assessment Model for Fitness for Work of Construction Personnel in Expressway Bridge Engineering Projects2026-99-15099/11/2026
To mitigate safety risks inherent in highway bridge construction, this research establishes a practical framework for assessing workers’ fitness for work. Using grounded theory, we analyzed interview records and documented accident cases through systematic coding, identifying critical indicators spanning physiological states, safety training effectiveness, and atypical behavioral markers. Rather than relying on single-method approaches, we combined Delphi expert consultation with entropy weighting to capture both professional judgment and data-driven variance, thereby reducing bias while preserving information richness. The resulting assessment protocol enables quantifiable classification of workers into distinct risk tiers. Implementation at the Zhangjinggao Yangtze River Bridge demonstrated the system's discriminatory power through field data collection and direct behavioral monitoring, successfully segmenting the workforce into low-, medium-, and high-risk categories. Results suggest the tool functions effectively as a pre-employment screening mechanism, allowing project managers to intercept potentially unfit workers before they enter hazardous work zones, consequently lowering the incidence of human-factor accidents.
Wu, Zhongguang, Dai, Junping, Ruan, Jing, Shi, Yonglong, Yuan, Zhenzhong, Hao, Jiatian
Effect Evaluation of Emergency Barrier-free Blocking Methods in Highway Tunnels Based on Visual/Driving Behavior2026-99-15319/11/2026
To address the lack of safe and effective on-site vehicle blocking and control methods in the event of fires or other emergencies in extra-long tunnels — which can significantly reduce traffic safety risks and prevent secondary accidents — this study proposes a novel barrier-free light–smoke curtain interception method. The method integrates conventional traffic safety warning facilities (gantry-mounted variable message signs and audio–visual alarms) with two light–smoke curtain interception images to form a composite early-warning and interception system. Driving simulation experiments were conducted to comprehensively evaluate its warning effectiveness, interception performance, and operational safety in comparison with methods employing only traditional warning facilities or light curtain images. Furthermore, field drills were performed to validate its real-world applicability and interception effectiveness under both daytime and nighttime conditions. The main findings are as follows: 1) The fixation ratio and interception success rate associated with the proposed method were significantly higher than those of the other two methods, demonstrating enhanced visual attention and superior warning and interception performance. 2) The maximum deceleration observed with the proposed method was lower than that of the light curtain–only method and did not trigger emergency braking, thereby indicating high operational stability and driver comfort. 3) In field drills, after activation of the interception equipment, only one and two vehicles entered the tunnel under daytime and nighttime conditions, respectively, and full control of on-site vehicles was achieved within two minutes without any traffic accidents, verifying the system’s rapid response and effective safety assurance.
Shi, Mingjun, Li, Shicao, Wang, Haohuan, He, Qifei, Che, Zhengzhang, Li, Yanbo
Emergency Rescue Resource Allocation Model and Reasoning Prediction Method for Expressway Reconstruction and Extension2026-99-15489/11/2026
During expressway reconstruction and extension, when a traffic accident occurs, how to make a scientific and reasonable allocation of emergency resources is the premise and basis for efficient rescue. In view of the reconstruction characteristics and the complexity of emergency rescue, the number of casualties, the damage degree of road facilities, the number of damaged vehicles, the range of hazardous chemicals, the size of the fire, and the traffic order were used as the accident attribute indexes to build a historical accident set (case database). The allocation of emergency rescue resources was predicted using case-based reasoning techniques. Also, the corresponding reasoning prediction method was proposed. The research shows that this model can accurately predict the demand for emergency rescue resources during the period of expressway reconstruction and extension, which has good availability and operability, and provides methodological and modeling support for the emergency rescue resource decision system.
Ran, Jin, Zhan, Shiyang, Kadir, Ahmetjan, Ma, Jiarui, Dai, Xiaomin
Research on an Evaluation Method and Application of Autonomous Vehicles in Traffic Flow Environment2026-99-15629/11/2026
Traffic flow environment testing is indispensable in the research and evaluation process of intelligent vehicles. However, the current vehicle evaluation systems mostly focus on simple dynamic scenarios and lack a comprehensive assessment of vehicle performance in complex traffic flow environments. In view of this, this paper constructs a multi-dimensional comprehensive performance evaluation system for vehicles in traffic flow environments. Firstly, based on the randomness and dynamics of traffic flow, four core evaluation dimensions covering safety, comfort, efficiency, and economy are constructed. In terms of security, the collision time and Predicted Safety Metrics are adopted. This enables the dual quantification of immediate collision risks and dynamic obstacle avoidance capabilities. The comfort evaluation focuses on the impact of vibration frequency on the human body and constructs a graded quantitative index. Efficiency and economy evaluation models are built through time cost and energy consumption cost. The verification is carried out under different traffic flow scenarios, and the final results demonstrate the consistency between the evaluation method of this paper and the expert evaluation method, thereby verifying the rationality of the evaluation system presented in this paper.
Wang, Guangyu, Song, Shiping, Zhang, Cheng, Qu, Ge, Yu, Xiaojun
Investigation into the Crashworthiness of Freight Vehicles under Frontal Impact2026-99-12869/4/2026
This paper investigates the crashworthiness of freight vehicles under frontal impact based on the C-NCAP (China New Car Assessment Program) standard. Explicit dynamics and finite element methods were employed to conduct simulation analyses of the impact event, with the aim of offering references for improving vehicle crashworthiness. The findings indicate that the vehicle cabin remains largely intact, providing sufficient survival space for occupants. However, increased load amplifies the impact impulse and reduces crashworthiness. Additionally, the use of an enhanced anti-collision beam helps distribute impact forces and lowers the peak impact load.
Liu, Zihan, Jiang, Yi, Wang, Pu
Influence of Restraint System Angles on Impact Response and Protection of Child Occupants in Vertical Crash Conditions2026-99-04138/28/2026
Focusing on the protection needs of child occupants in the scenario of aircraft vertical crashes, a finite element calculation model based on the cabin structure of a certain type of small electric aircraft was established. The child seat restraint system was coupled with the THUMS 3YO human body model, and the vertical 15 g condition meeting the requirements of Article 23.562 of CCAR-23-R3 was simulated. The influence law of the safety belt restraint angles (formed by different safety belt routing positions) on the dynamic response and injury indicators of child occupants was explored. To verify the rationality of the simulation results, a physical impact experiment was conducted using a Hybrid III 3YO child dummy and the same type of child seat, with key indicators (e.g., head acceleration, lumbar load) measured and compared with simulation data. The analysis results show that the effect of the safety belt restraint angle on the overall protective performance is less pronounced under vertical conditions, but a clear trend is observed: when the angle is in the range of 76°~84°, the head acceleration is relatively low and the brain tissue injury indicators are in the optimal state, which can effectively reduce the risk of head and neck injuries; when the restraint angle increases to 92°, the lumbar axial load and lung strain increase significantly, indicating a detrimental effect. The results of this study clarify the differences in the protective performance of child seats under different restraint angles, and provide a theoretical basis and technical guidance for the layout of safety belt anchors of aircraft seats and the optimal design of child seats.
Wang, Yafeng, Guo, Pan, Li, Weiliang, Shi, Xiaopeng
Dynamic Response and Energy Absorption of a Novel Arc-Shaped Hourglass Re-Entrant Honeycomb under Impact Loading2026-99-04178/28/2026
This study introduces an arc-shaped hourglass re-entrant auxetic honeycomb (AHRH) and examines its impact-induced dynamic response and energy-absorption behavior via finite-element simulations. The conventional re-entrant honeycomb (RH) is adopted as the baseline, and side-by-side simulations are performed at impact speeds of 10, 20, and 30 m/s. The mechanical response of both lattices is assessed through force-displacement characteristics, absorbed-energy histories, and representative deformation modes. Results indicate that the AHRH significantly reduces the initial peak force, prolongs the plateau stage, and exhibits a distinct dual-plateau feature, thereby achieving the desirable crashworthiness mode of “low initial peak-extended plateau-high densification”. Compared with the RH, the AHRH achieves increases of approximately 42.9%-59.7% in total energy absorption and 42.8%-56.1% in specific energy absorption while maintaining nearly identical mass. The enhanced performance arises from the arc-edge geometry, which alleviates local stress concentrations, promotes progressive buckling, and generates multiple plastic hinges. These mechanisms lead to smoother load transfer, avoidance of excessively high initial impact loads, and more efficient crash energy management. Overall, the proposed AHRH structure demonstrates superior energy absorption capacity and deformation stability compared with the conventional RH, providing new insights and practical references for the lightweight design and optimization of advanced protective and crashworthy structures.
Jiang, Zhide, Chen, Long, Yu, Ping
Stress Analysis and Simulation Study of Propane Spherical Tanks2026-99-03348/14/2026
As special pressure-bearing vessels, spherical tanks are widely used in chemical, oil refining, and other fields. However, their safe operation faces the dual challenges of structural failure and leakage diffusion. Meanwhile, due to its low lower explosive limit and the low ignition energy required, propane will evaporate rapidly after leakage to form an explosive mixed gas, which may further trigger severe accidents such as combustion and explosion. Therefore, this paper takes a 3000 m3 propane spherical tank as the research object, comprehensively applies the finite element analysis method, and systematically researches stress distribution, aiming to provide theoretical support for the safety design of spherical tanks and accident prevention and control.
Huang, Yuanxuan, Tao, Gang, Zhang, Lijing
Pelvis Lap Belt Engagement of Small-Sized Females in Frontal Impacts Using Seat-Integrated Restraints and Vehicle Seats for Alternative Seating Positions2026-22-00088/14/2026
Non-traditional vehicle seating postures challenge traditional occupant protection paradigms that promote pelvis lap belt engagement. Seat-integrated restraints may promote pelvis lap belt engagement in alternative seating postures but have not been evaluated with post-mortem human subjects (PMHS) in vehicle seats. The goal of this research was to perform three 38.8 g, 56 km/h frontal impact sled tests with small-sized female PMHS in a crash environment with a vehicle seat designed for alternative seating positions. PMHS pelvis kinematics, lap belt engagement, and submarining response were compared to that of the Hybrid III 5th female (HIII-5F) in the same environment. The seat was in the rearmost seat track position, reclined 40° from vertical, and incorporated a leg rest, which elevated the feet off the floor. A seat cushion airbag (SCAB), large passenger airbag (PAB), shoulder belt pretensioner (SB P/T), and seat-integrated belt (BIS) were incorporated into the testing environment. The SCAB restricted initial downward translation of the pelvis and induced 7.7°–11.8°of initial pelvis rearward rotation. Lap belt loading of the abdominal soft tissue occurred in each test via three distinct interactions: (1) initial pelvis lap belt engagement followed by pelvis fracture and subsequent submarining; (2) lack of initial pelvis engagement and direct abdominal loading; (3) initial pelvis lap belt engagement followed by submarining. In a matched test environment, the HIII-5F did not submarine nor reproduce the entire lap belt pelvis interactions observed by the PMHS. Future research must develop better tools for predicting lap belt engagement in alternative seating positions.
Newman, Rachel, Shin, Jeesoo, Sochor, Sara, Morgan, Neal R., Gepner, Bronislaw D., Kerrigan, Jason R., Kim, Yongtae, Kim, Sung Rae
Relevant vehicle front-end components for pedestrian laboratory testing to address real-world pedestrian injuries when struck by passenger vehicles with high hood heights2026-22-00098/14/2026
In the United States, pedestrian deaths account for 18% of roadway fatalities and have increased 78% since their lowest point in 2009. U.S. consumers are increasingly purchasing larger vehicles that are responsible for a disproportionate number of pedestrian injuries. This study examined a dataset of pedestrians struck by passenger vehicles in Michigan from 2015 to 2024 to identify the unique characteristics of the tallest vehicles, large SUVs and pickups, which are contributing to increased injury. Vehicle height was categorized as the hood leading edge (HLE) height compared with the estimated pedestrian hip and waist heights from anthropometric measures. Maximum abbreviated injury scale and injury sources by body region were tabulated for three vehicle height categories. Typical kinematic patterns were observed for each relative height category and the corresponding injury frequency and impact locations. For vehicles with high hood heights, head and torso injuries were commonly from the front of the vehicle —the grille, headlights, and HLE. In contrast, head injuries sustained when pedestrians were struck by medium-height and short vehicles were primarily from the vehicle hood and windshields. Even among the tallest vehicles where the bumper was much higher than the pedestrian’s knee, leg injuries from the vehicle bumper and valance were frequent, suggesting that evaluating these vehicle components is also necessary to address lower extremity injuries. This study identified the unique pedestrian impact locations associated with the tallest vehicles, which can help guide vehicle designers when considering impact attenuation strategies to reduce injury in crashes with pedestrians.
Mueller, Becky, Jermakian, Jessica
A Driver Behavior Detection Method Based on Improved YOLOv11 and an Attention Mechanism2026-01-50468/6/2026
Driver’s distraction and fatigue are among the major contributing factors of traffic accidents. This study presents a methodology to identify driver’s distraction using a refined You Only Look Once (YOLO) model, denoted as YOLOv11.To address the inconsistent performance of earlier versions of YOLO, especially with regard to lack of systematic evaluations, this study proposes an improved YOLOv11 model. A mixed local channel attention (MLCA) module is further introduced to enhance small object feature extractions considering the use of Wise-Intersection over Union (IoU) v3 loss function to improve localization accuracy and training stability. Experiments demonstrated that this model outperforms competing models across all metrics, achieving 99.13% mAP at 0.5 and 82.54% mAP at 0.5:0.95, while also achieving minimal bounding box loss. The proposed model demonstrated higher accuracy and robustness, making it suitable for real-world driver monitoring system (DMS) deployments.
Ma, Bao, Taghavifar, Hamid, Fu, Zhijun, Karangwa, Jules, Rakheja, Subhash
Optimization of Pneumatic Conveying Elbows to Reduce Grain Particle Normal Contact Forces via CFD-DEM Coupling Method2026-99-01167/31/2026
This study presents a refined design for pneumatic conveying pipelines, featuring a grooved structure at the bend aimed at reducing particle breakage during transportation. Using soybean particles as a focus, the research employs a gas-solid two-phase flow approach to explore how different groove depths and widths influence the breakage rate. We used CFD-DEM simulation techniques, combining fluid mechanics with discrete element modeling to achieve a more accurate representation of particle motion and collision forces during expressing. Based on these simulations, we identified the most effective combination of groove width and spacing. Experimental results showed that a groove width of 4.5 mm coupled with a 40 mm spacing could decrease impact forces on particles by approximately 5% to 10% at expressing speeds of 15 m/s and 20 m/s. Throughout all measured time intervals, the impact forces remained stable, with turbulence exerting minimal influence on the particle forces.
Luo, Xinhao, Yang, Tiancheng, Huang, Bo, Mao, Genwu, Dong, Deliang, Shi, Heng, Li, Xiaoliang, He, Bo
Collapse Strength and Crush Space Analysis in Lateral Side Pole Impact of an Electric Vehicle2026-01-50527/31/2026
High-Voltage Battery (HVB) protection in lateral pole impact is very important due to severe nature of the impact. Unlike frontal impacts, vehicles have limited range of space and capacity to absorb kinetic energy in lateral side impacts. Nowadays, computer-aided engineering (CAE) using finite element analysis (FEA) is utilized routinely to simulate high-speed crash events of varied type, including side pole impact. These CAE applications focus on the analysis and design of HVB when the vehicle structure is well-developed. CAE methods are time-consuming and are not suited during the pre-program stage when the structure is only in a concept stage and not even a reasonable CAD is available/developed in any sense to use these methods. There is no analytical tool available to understand how to define the characteristics of the structure that surrounds and protects the HVB. The primary motive of this publication is to help with this aspect of vehicle planning/development. Needless to state that this procedure can also be used in planning/developing of internal combustion engine (ICE) and hybrid vehicles, as well. The objective therefore is to develop a simple method/procedure that can give reasonably accurate estimation of the collapse/crush force required for a specified crush space and hence protect the critical components, such as HVB and fuel tank. This analytical method also gives some insight into the optimal use of the upper body (rocker and floor cross-members) and underbody (ladder frame) parts. It was found, for a problem under consideration, optimum kinetic energy to be absorbed by the upper body is 32.5% to avoid intrusion into HVB.
Alavandi, Bhimaraddi, Midoun, Djamal, Frank, Randy
Analytical Analysis of Wellbore Stresses under Fluid Pressure and In-Situ Stress in Three-Dimensional Wellbores2026-99-08317/30/2026
During fluid injection operations such as fracturing and well killing, the casing, cement sheath, and borehole wall rock are subjected to three-dimensional in-situ stresses and internal pressure. If the equivalent stress exceeds the material’s yield strength, component failure may occur, leading to wellbore failure or even blowout accidents. In order to investigate the stress distribution in wellbores under specific working conditions, a three-dimensional mechanical model of curved wellbores was established. By adopting the superposition principle and stress function method, the influence of horizontal in-situ stress non-uniformity on the fourth equivalent stress of various components was analyzed. The study demonstrates that under three-dimensional in-situ stress, the fourth equivalent stress of each component increases with the rise of horizontal in-situ stress load non-uniformity and azimuth angle. Meanwhile, borehole azimuth angle and in-situ stress load non-uniformity exert a greater influence on the fourth equivalent stress of the casing, while internal pressure has a lesser impact on it. The effects of azimuth angle, horizontal in-situ stress load non-uniformity, and internal pressure on the fourth equivalent stress of the casing are more significant than those on the cement sheath and borehole wall rock. The research results can provide theoretical and technical references for wellbore design and safety improvement, as well as for the structural safety assessment of components such as automotive chassis and body frames under complex dynamic loads.
Zhang, Wenzhe, Jiang, Wu, Guo, Ziwang, Cao, Yinping, Dou, Yihua
Structure Optimization of a Two-Dimensional Mixer for Mixing Uniformity Improvement Using the DEM2026-99-08467/30/2026
A two-dimensional (2-D) mixer has been widely used in the engineering field. The discrete element method (DEM) is capable of simulating and tracking collisions among particles inside the mixer. In this paper, the mixing process of spherical particles inside a 2-D mixer known as EYH150L is simulated by the DEM. The Lacey Index provides a quantitative measure of the blending efficacy achieved by a 2-D mixer. The DEM analysis indicated that the level of blending effectiveness among the particles in proximity to the rotating blades is significantly superior to that in regions devoid of blades. The rotational velocities of particles in blade-free zones are about 40% of those near the rotating blades, which serves as a key factor accounting for the slower increase in mixing efficiency observed in these regions. To address this disparity and enhance overall mixing performance, a mirrored rotating blade was incorporated, positioned to the left of the baseline revolving cylinder, thereby optimizing the structural configuration of the 2-D mixer. The verification tests indicated that the modification increases the mixing efficiency of the mixer at its left side, and enhances the blending uniformity, ensuring the four particle types are mixed equitably.
Fang, Ziqiang, Liu, Yong, Chen, Yafeng
Comparison of Female and Male Post Mortem Human Subject Kinematic Responses and Injuries in Rear-Facing Seat Configurations in High-Speed Frontal Impacts2026-22-00077/28/2026
This study investigates female post-mortem human subject (PMHS) responses and injuries, comparing them to previously published data from male PMHS tested at a change in velocity (delta-V) of 56 kph in high-speed rear-facing frontal- impact (HSRFFI) scenarios. Twelve small female PMHS were subjected to the same HSRFFI pulse. The subjects were positioned in reinforced production seats, identical to those from the previous male PMHS studies, and set to recline angles of either 25 or 45 degrees. Instrumentation was used to measure kinematics of the head, spine, pelvis, and ribs. Whole-body kinematics were recorded using motion capture. Female PMHS consistently showed lower head restraint, seatback, and lap belt loads compared to males across all test conditions (Bio Rank System [BRS] scores >1.0), with BRS scores for head restraint forces as high as 4.0. While head and T1 kinematics were consistent with males in all-belt-to-seat (ABTS) conditions (BRS < 1.0), significant differences were found in other body regions (BRS>1.0). Female PMHS had larger head forward rotation and smaller pelvis Z-axis displacement (less ramping) than males in the fixed D-ring (FDR) conditions, leading to major discrepancies (BRS>2.0). In addition, female chest deflection was smaller in one FDR condition (BRS=1.98), and tibia acceleration onset was earlier. Female PMHS sustained severe to critical rib fractures (Abbreviated Injury Scale [AIS]3-5) similar to males. However, five females in the FDR conditions and one in the ABTS condition sustained sacral fractures, an injury not seen in males. Females also had a higher frequency of lower extremity fractures (7 of 12) and vertebral body fractures (7 of 12) compared to males. These findings suggest that existing male PMHS data may not adequately predict responses and injury risks for female PMHS, emphasizing the need for female-specific biomechanical data to enhance safety tools and models in HSRFFI scenarios.
Kang, Yun-Seok, Baker, Gretchen H., Ramachandra, Rakshit, Marcallini, Angelo, Kwon, Hyunjung, Foster, Craig D., Moorhouse, Kevin, Agnew, Amanda M., Bolte, John H.
Geometric Deep Learning–Based AI Framework for Nonlinear Crash Behavior of Extruded Rails15-19-03-00127/27/2026
Extruded Rails are critical energy-absorbing components in automotive structures designed to mitigate impact loads during the frontal collisions. Traditional crashworthiness design relies heavily on computationally expensive finite element simulations and iterative design exploration. This work proposes a machine learning–driven framework for rapid front extruded rails design using a trained geometric deep surrogate model. A design-of-experiments (DoE) was conducted by varying geometric parameters including width, height, and wall thickness of a thin-walled extruded rail structure. For each design variant, LS-DYNA simulations were performed to obtain performance metrics such as mean crush force and peak crush force. These simulation results were used to train an AI surrogate model capable of predicting crash responses directly from geometric parameters. The proposed approach significantly reduces computational cost by replacing repeated high-fidelity crash simulations with machine learning surrogate predictions. By enabling fast and accurate evaluation of crash response metrics, the workflow shortens design cycles and supports sustainability-driven crashworthiness assessment by reducing simulation resource usage. The framework establishes a scalable, simulation-driven engineering pathway across vehicle platforms and provides a foundation for future closed-loop, AI-assisted crash design workflows.
Kumar, Manik, Srinivasan, Sriram
Study on Cleaning Requirements and Verification Methods for Oxygen Equipment of a Certain Type of Civil Aircraft2026-99-18037/17/2026
Pollution in the oxygen system of civil aircraft may lead to fire accidents, and maintaining the cleanliness of oxygen equipment is the most effective measure to reduce the risk of fire. This paper introduces the cleanliness requirements, cleaning methods, and procedures of oxygen equipment, and combines the cleanliness level requirements of oxygen equipment for a certain type of civil aircraft. By detecting the total weight of Non-Volatile Residue and the size and quantity of particles on the surface of the parts, it verifies whether the specific cleaning process can meet the cleanliness level required by the design. In addition, the possible sources of pollutants are analyzed based on the first unqualified verification results, and targeted improvement directions for the process are provided. After re-performing the cleanliness verification test, the results passed successfully, indicating that the process improvement is effective and has passed the airworthiness certification of the reviewer.
Huang, Jingqi
Experimental Analysis of Human Head Dynamic Response and Injury under High-G Landing Shock2026-99-18617/17/2026
This study looks at how the human head reacts and gets injured during high-G landing impacts in spacecraft return capsules. We used a vertical drop tower system for the experiments. A standard crash test dummy, called the Hybrid III 50th, was used to imitate how astronauts sit during landing. We applied two common safety standards—the Head Injury Criterion (HIC) and the 3 ms cumulative acceleration rule—to measure head response under high-G impacts. The results show several things. First, head acceleration increases linearly as seat acceleration increases. Second, the peak total acceleration of the head is much higher than the seat acceleration. In particular, acceleration in the X and Z directions is much stronger than in the Y direction. Third, when seat acceleration went over 47.71 g, HIC exceeded the safe limit of 700, and the 3 ms head acceleration also passed the 80 g limit. This suggests that 40 g should be considered a safe upper limit for seat acceleration. This work provides experimental support for improving landing systems to protect astronauts’ heads during high-G impacts.
An, Hao, Wang, Yafeng, Guo, Yazhou
Fifteen Instrumented Motorcycle Crash Tests into a Barrier and Stiffness Comparison of Standard and Upside-Down Forks2026-01-50597/10/2026
Fifteen instrumented crash tests were performed using a 2005 Yamaha R6 motorcycle. Seven tests were performed with upside-down (USD) forks and eight tests were performed with standard forks. The 2005 Yamaha R6 provided a platform where both types of front forks could be interchanged. For all tests, the motorcycle was delivered into a concrete block at speeds varying between 5 and 23 mph. Seven tests were conducted at low speeds to determine the onset of permanent deformation. Eight tests were conducted at higher speeds to observe the wheelbase reduction of the motorcycle and its relationship to impact speed. This paper summarizes the data from these tests related to wheelbase reduction, impact dynamics, and post-impact movement, allowing comparison between two different suspension systems and historical datasets.
Lucernoni, Anthony, Boyd, Dusty, Wahba, Ronny, Taeuber, Andre, Stoner, Jacob, Law, Trevor
Multi-Objective Optimization Research and Design of Seat Structure in Vehicle Collision2026-99-05187/10/2026
The vehicles often accompanied by a huge impact in the collision process, high-quality and high-strength car-seats can better protect the safety of passengers. However, in the call for vehicle energy saving and emission reduction, the lightweight design of car-seats is imminent. Therefore, it is necessary to achieve lightweight seat weight while ensuring vehicle safety. Based on the dynamic condition of vehicle collision, this paper takes the rear seat of a certain model as the research object, takes multiple responses of the seat skeleton system as the target, establishes a multi-objective optimization model of the seat skeleton, determines the optimization result with the greatest comprehensive satisfaction, verifies the optimization result of the seat skeleton. The correctness and feasibility of the design method are proved.
Shao, Youlin, Ni, Weiyu, Chen, Daojiong, Cheng, Zhiqing
Research on the Design of Lane Line Recognition and Deviation Warning System Based on Machine Vision2026-99-05667/10/2026
In order to reduce traffic accidents caused by cars straying from lanes, a lane line recognition and deviation warning system based on machine vision is designed. It mainly includes image preprocessing, lane line detection, and the design of a deviation warning model. “In this study, an ROS-based intelligent vehicle-mounted camera is adopted for road image collection. To reduce the computational load of data processing while guaranteeing the algorithm’s accuracy and reliability, grayscale conversion and region of interest (ROI) extraction are implemented to finish the image preprocessing stage. Additionally, a fusion strategy of global and local thresholds is introduced to enhance both the operational speed and detection accuracy of the algorithm” use the Canny operator for the edge feature extraction; and complete the fitted lane lines with the improved Hough transform. Finally, based on the Kalman filter and camera viewpoint conversion coefficient algorithm, the lane line offset is detected in real time, and the deviation is judged in combination with the monitoring interface. Simulation experiments show that the system is able to effectively recognize the lane line and judge the deviation status under the condition of setting the offset threshold of 70 pixels, which significantly improves the accuracy and real-time performance of the lane deviation warning and provides effective technical support for reducing traffic accidents.
Wang, Xufeng, Zhang, Chunshu, Wang, Yan, Chen, Yihui, Ji, Rui
Optimization Method for Emergency Rescue Resource Allocation in Two-Way Ten-Lane Expressway Based on Risk Assessment2026-99-05677/10/2026
The two-way ten-lane expressway has the significant characteristics of “large traffic volume, mixed vehicle types, and heavy loads”, which makes the impact of traffic flow status on accident risk present nonlinear characteristics. Traffic flow fluctuations not only directly affect the probability of accidents, but also amplify the spatiotemporal differences in rescue needs through mechanisms such as lane occupancy time and accident chain reactions. Therefore, the essence of resource allocation on a two-way ten-lane expressway is the “spatiotemporal matching problem between dynamic risks and limited resources”, which requires both quantifying the spatiotemporal evolution of risks and coping with the high uncertainty of the traffic system. Aiming at the problem of inefficiency of traditional empirical resource allocation under complex traffic conditions, this study proposes a dynamic optimization framework based on multidimensional risk assessment for emergency rescue resource allocation. In this framework, firstly, the entropy weight method and fuzzy comprehensive evaluation are combined to construct a risk quantification model using historical accident data and real-time traffic characteristics to achieve fine risk classification of road sections. Secondly, a multi-objective optimization model is established with the goal of minimizing risk-weighted costs and maximizing risk-weighted resource demand satisfaction, and considering constraints such as mandatory requirements for key equipment in high-risk areas and minimum site configuration. At the same time, the improved NSGA-II algorithm is used to effectively solve the contradiction between cost and utilization efficiency in emergency rescue resource allocation through adaptive non-dominated sorting, hybrid genetic operators and dynamic penalty mechanism. Experimental results show that the improved NSGA-II algorithm is superior to the traditional method in terms of Pareto front distribution, convergence speed and actual resource allocation effect. Compared with the traditional scheme, the method proposed in this study reduces the resource allocation cost by 35.5%, increases the risk-weighted resource demand satisfaction rate by 1.9%, and expands the resource coverage of high-risk areas by 13.8%. This study provides scientific decision-making support for emergency response in complex road networks and offers a practical optimization approach for highly dynamic traffic emergencies.
Kan, Youjun, Cao, Yang, Shi, Xiaomin, Gao, Shangjie
Traffic Crash Prediction and Causal Disentanglement by Machine Learning2026-99-05527/10/2026
Aiming at the problem of insufficient modeling of spatio-temporal heterogeneity in road traffic accident prediction, a dual task machine learning framework integrating geographical environment, location attributes and time periodicity is proposed. The dataset used in this study was derived from traffic accident records of Nanchang during 2019–2023. Firstly, geographical identifiers are generated by rounding and aggregating latitude and longitude coordinates. At the same time, the location type is processed by a one-hot encoding, so as to carry out spatial clustering analysis of accident hotspots. Compared with the North-South pattern, the contribution of geographical features shows a strong East-West trend. The kernel density heatmap identified Zone A and zone B as dual core high-risk areas. Secondly, the sinusoidal/cosine function is used to encode the time feature circularly, which effectively captures the daily change of the accident. The quantitative analysis of random forest regression model showed that time characteristics accounted for 89.2% of the variance of accident frequency interpretation, significantly exceeding the contribution of geographical factors (10.2%) and location attributes (0.6%). After hyperparameter optimization, the accuracy of XGBoost classifier in predicting serious accidents is 75.97%, and the AUC value is 0.8412, which has strong robustness, and provides reliable support for dynamic risk assessment of traffic management system.
Luo, Jiang, Zhang, Yuxin, Li, Xin, Wu, Ronghai
Privacy-Preserving UAV-Based Traffic Data Acquisition Platform2026-99-05957/10/2026
This paper puts forward a Privacy-Preserving UAV-Based Traffic Data Acquisition Platform to address 1) privacy leakage, 2) limited scenario coverage, and 3) low traffic data utilization efficiency in urban traffic monitoring environments. Our system integrates three innovations: 1) Dynamic Privacy Masking (DPM) and Dual-Track acquisition (DTC), which hides sensitive information (e.g., faces, license plates or LPL) in real-time while preserving critical traffic data (e.g., vehicle density, speed), 2) traffic data Localization (DL) and Privacy-Enhanced Federated Learning (FEFL), enabling cross-regional collaboration without raw traffic data sharing by perturbing neural network updates with differential privacy (DP), and 3) Ground-Air Collaboration (GAC) and VPF (VPF), combining UAVs with ground sensors and digital twins (DTs) to cover blind spots (e.g., tunnels, extreme weather). Experimented on UA-DETRAC and CitySim traffic data-sets, the platform achieves 92% privacy compliance (GDPR/PIPL), 87.5% mAP accuracy, and 85% road network coverage, outperforming other methods (e.g., FedUAV, static blurring). It supports applications such as traffic flow optimization, accident prevention, and regulatory alignment.
Zhang, Shilin, Yan, Ming
A Framework for Precautionary Safety for Automated Driving Systems—Toward Tactical Decisions Fulfilling Quantitative Risk Acceptance Criteria12-09-04-00287/8/2026
Safety of Automated Driving Systems (ADSs) is arguably one of the main remaining barriers before widespread market deployment. While there exists a plethora of methods for planning a trajectory that fulfils certain constraints, what those constraints should look like, to enable effective planning of safe trajectories, is still being discussed. In this article, we generalize the concept of Precautionary Safety (PCS) and present a framework providing constraints on the tactical and operational decisions of the ADS. Such constraints consider the ADS’ capabilities, the external conditions, knowledge of statistically relevant events and behaviors of other traffic actors, as well as the controllability of these events. The proposed framework enables assessment of the statistical fulfilment of quantitative risk acceptance criteria (QRACs), including requirements on accident, injury, and fatality rates. The framework further provides a means to dynamically adapt the constraints used for trajectory planning, i.e., to adapt the driving to the situation at hand. A case study, considering a possible collision scenario with a jaywalking pedestrian and a rear-end collision with a trailing vehicle, is provided to showcase the applicability and usefulness of the presented framework. The simulation-based case study displays the safety benefits from considering QRACs with multiple injury risk levels and further shows how the proposed PCS framework can be applied in practice.
Gyllenhammar, Magnus, de Campos, Gabriel Rodrigues, Sandblom, Fredrik, Törngren, Martin, Fredriksson, Jonas
The Influence of Spatial and Aspatial Factors on the Safety Driving Behavior of Motorcycle Couriers in the Gig-Economy Era: A Case Study of East Jakarta, Indonesia09-14-02-00057/3/2026
This study aims to analyze the impact of spatial and aspatial factors on the safety driving behavior of motorcycle couriers in East Jakarta within the context of the gig economy. Both factors are integrated to clarify how spatial conditions and individual characteristics jointly shape couriers’ safety driving behavior. The Partial Least Squares Structural Equation Modeling (PLS-SEM) method was employed to examine the relationship between spatial and aspatial factors on safety driving behavior. Data were collected through questionnaires from 253 motorcycle couriers operating in three subdistricts in East Jakarta, namely Cakung, Pasar Rebo, and Pulo Gadung. The results show that safety driving behavior is significantly influenced by aspatial factors, particularly socioeconomic characteristics and personality traits. In contrast, spatial factors such as road conditions and daily activity patterns do not directly influence safety driving behavior, but exert indirect effects through the couriers’ personality traits.
Wahyuddin, Yasser, Sitorus, Paldibo Alfriramson, Putri, Kharunia, Maharani, Garnierita
An Analysis and Comparison of Free-Space Detection Approaches and Their Evaluation for Heavy-Duty Vehicles2026-01-07637/1/2026
The detection of free space plays a fundamental role in ensuring the safe and efficient operation of heavy-duty vehicles, particularly in environments where the available area to maneuver is severely constrained, such as construction zones, rest areas, or loading docks. An accurate estimation of free space is essential to prevent collisions, maintaining operational continuity and minimizing vehicle downtime. As observed from the reviewed literature, despite the large number of proposed free-space detection methods, there is no concise and established definition about how free space should be determined, represented, and inferred, nor agreement on the semantic classes to be considered. This heterogeneity complicates systematic comparison and benchmarking across approaches. This paper presents a structured survey and methodological analysis of recent free-space detection and semantic segmentation approaches across automotive LiDAR-, camera-, and radar-based perception systems, as well as multimodal sensor fusion. The review spans classical geometric and occupancy-based techniques together with deep-learning methods, along with datasets commonly used for evaluation. The main contributions are (i) a structured taxonomy and comparative analysis of existing free-space definitions and detection strategies, categorized by their assumptions, representation forms, and sensing modalities; and (ii) a unified and application-independent definition of free space together with the required semantic classes. These contributions aim to provide a consistent conceptual foundation to support future research and to aid the systematic evaluation of upcoming free-space detection systems.
Martinez, Cristian, Peters, Steven
Model-Guided Scenario Expansion for Data-Driven Autonomous-Vehicle Safety Testing: A Feasibility Demonstration12-09-04-00326/29/2026
This article presents a data-driven pipeline for autonomous-vehicle (AV) safety testing. The pipeline integrates real-world traffic observations with model-guided scenario expansion and safety-metric evaluation to enable an end-to-end AV safety testing framework, demonstrated on a canonical highway scenario. The framework enhances test diversity, realism, and coverage by generating statistically informed variants of observed driving behaviors. Key parameters such as vehicle speed, trajectories, and headways are extracted from naturalistic data and used to train a probabilistic model of traffic dynamics. Scenario variants are sampled from this model and encoded as behavior trees (BTs) for modular, simulation-ready execution. Each scenario is simulated using a consistent AV control configuration, and safety metrics such as minimum safe distance violation, minimum safe distance factor, time to collision, and aggressive driving are applied to evaluate safety outcomes independently of system-specific tuning. A case study based on the highD dataset (110,000+ trajectories) demonstrates the framework’s ability to generate realistic and safety-relevant scenarios, providing an initial demonstration of pipeline feasibility and metric-based evaluation. This initial study is intentionally scoped to a single scenario class and a simplified parametric model to isolate and validate the end-to-end integration of the pipeline.
Elshenawy, Mohamed, Aboudina, Aya, Abdelmotaleb, Anhar, Amr, Mariam, El-darieby, Mohamed
Female PMHS Thoracic Biomechanical Response Corridors with Preliminary Consideration of the Influence of Breast Tissue in Frontal Impacts2026-22-00066/24/2026
Thoracic injuries are common for belted occupants in frontal motor vehicle crashes. However, there remains a lack of female post-mortem human subject (PMHS) data in the literature to generate female-specific biomechanical response corridors and evaluate engineering tools such as anthropomorphic test devices (ATDs) and computational human body models (HBMs). Additionally, the effect of breast tissue on thoracic response has not been directly investigated despite female ATDs and HBMs having features representing breasts. As such, this study sought to utilize simplified frontal hub impacts to (1) generate female PMHS thoracic response corridors both with breasts positioned with a bra and without breasts (no bra) and (2) preliminarily explore the influence of breasts on the thoracic responses of female PMHS. Twelve female PMHS (9 small and 3 midsize) were subjected to frontal impacts at mid-sternum with a 14.0 kg circular impactor at 4.3 m/s in conditions with and without breasts. Force versus deflection (FD) response corridors were generated, and comparisons were made between groups and to scaled FD corridors representing female response. Overall, female PMHS with and without breasts displayed differences in FD response compared to scaled corridors in terms of the shape of the initial response and peak force and deflection. Additionally, female PMHS with breasts produced lower peak force and greater peak deflection compared to those without breasts. These results suggest the importance of collection and evaluation of female biomechanical data that can be used for continued evaluation of female-specific safety tools as well as the further reduction of injury risk for all occupants during motor vehicle crashes.
Baker, Gretchen H., Kang, Yun-Seok, Marcallini, Angelo, Lang, Ryan, Hutter, Erin, Moorhouse, Kevin, Agnew, Amanda M.
Comparison of Concussion Risk Functions Generated from Two Different Datasets2026-22-00046/11/2026
To estimate risk of concussion, risk functions based on injuries occurring in sports are often used. A range of datasets have been used to develop injury risk functions for concussion based on either global kinematics or tissue-level predictors. Two such datasets are one from American football, and another one from Australian football and rugby. These two datasets constitute the largest published collections of video-verified concussive cases in sports with known kinematics suitable for constructing risk functions. The objective of this study was to analyze the differences between two datasets of concussion for injury predictions to better understand the influence on injury risk functions. The kinematics were applied to the KTH head model and risk functions for different kinematic- and tissue-based predictors were developed and compared. The accuracy, sensitivity, specificity, and AUC were also compared. The two datasets evaluated in this study generated different risk curves. The datasets had some similarities such as having no significant difference in resultant linear acceleration, but also some differences, for example having a significant difference in resultant angular velocity. The Australian cases had relatively equally distributed major x-, y-, and z-components for angular velocity while the majority (59%) of the NFL cases had a major x-component (coronal plane rotation) representing more than 50% of the resultant. The y-component of the linear acceleration (lateral direction) was the major component in 64% of the Australian cases and 72% of the NFL cases. The two datasets, from Australian football/rugby, and American football, generated different injury risk curves with a lower 50% risk of concussion for the Australian dataset. This indicates that the choice of data as input for the development of injury risk functions is important. Therefore, it is necessary to improve methodology with focus on sampling methods and reliable/valid data collection.
Fahlstedt, Madelen, Meng, Shiyang, Patton, Declan, McIntosh, Andrew S., Kleiven, Svein
Influence of Joint Structure in Multibody Model on Behavior Analysis of Crash Test Dummy2026-22-00056/11/2026
This study developed a new multibody model that accurately represents the collision behavior of crash test dummies using PC-Crash. The model replicates the shape and weight of an actual dummy. To investigate the influence of joint structures on collision behavior, an additional multibody model was developed to reproduce the joint structure of the actual dummy. These models were applied to analyze occupant behavior in a full-frontal rigid barrier and pedestrian behavior in a vehicle-to-pedestrian impact experiments. A comparison of the multibody model simulations with actual dummy impact experiments revealed that the behavior of the multibody model, which simulates the joint structure of the dummy, closely matched that of the actual dummy. The results indicate that joint structure significantly influences collision behavior, and accurately recreating it improves the precision of crash test dummy collision behavior analysis using PC-Crash.
Usui, Masatoshi, Matsui, Yasuhiro, Hosokawa, Naruyuki, Tanaka, Yoshinori
A Comprehensive Review of System Risk in Automotive Crash Safety15-19-02-00106/9/2026
Occupant protection has been at the forefront of risk evaluation regarding vehicle crashworthiness design. However, the vehicle is a member of a larger transportation system with varied stakeholders. This article identifies an opportunity for assessing risk in a crash event through emerging safety science paradigms. Conventional Safety I and Safety II frameworks handle well-defined hazards but falter with uncertainty, variability, and emergent behaviors in real crashes. A comprehensive literature review was performed on peer-reviewed research to situate automotive crash safety risk within the Safety III paradigms. The review addresses two questions: (1) How is “risk” defined across the crash safety literature and adjacent safety science domains? and (2) What limitations arise from these definitions in practice? Findings show a dominant probabilistic framing alongside a minority of system-oriented interpretations. Current crash safety practice lacks a coherent, system-level definition of risk that integrates uncertainty and knowledge strength, leading to fragmented methods and limited alignment with modern safety science. Based on this synthesis, the article proposes guiding principles for Safety III-aligned guidelines and recommendations that integrate consequences, uncertainty, and knowledge strength to improve transparency, traceability, and adaptability in crash safety decision-making.
Rye, Patrick J.
Monitoring Hydrogen Fuel Quality in Real TimeTBMG-552816/1/2026
The Korea Research Institute of Standards and Science (KRISS, President: Dr. Lee Ho Seong) has developed equipment that monitors the quality of hydrogen fuel supplied to vehicles through hydrogen refueling stations in real-time. This equipment is expected to prevent hydrogen vehicle accidents caused by impurities in the hydrogen fuel and improve the quality of hydrogen production.
Traumatic Brain Injury in Vulnerable Road Users: Analysis of German In-Depth Crash Data to Inform Targeted Prevention2026-22-00035/28/2026
Road traffic crashes are a major cause of traumatic brain injury (TBI), particularly among vulnerable road users (VRUs). However, current injury prevention strategies often overlook the heterogeneity of TBI—which include various injury types and severities—leading to an oversimplified approach to evaluating helmets and safety systems in regulations and ratings. To identify priority TBI types and severities in VRUs and to inform targeted prevention strategies, the German In-Depth Accident Study database was analyzed and a pathoanatomic classification system, i.e., Abbreviated Injury Scale, was employed. AIS 2 (moderate) TBIs account for 70-80% of all brain injuries across VRU groups, nearly half of which are concussions. For helmeted cyclists, milder TBIs are at a greater percentage than for unhelmeted cyclists. These findings highlight the need for expanding prevention efforts to include AIS 2+ injuries. Key injury types observed include concussion (with and without loss of consciousness), skull base fracture, subdural hemorrhage, contusion and laceration. New mechanism-specific injury criteria may be needed to address these injuries. The strong similarity in injury type ranking among different road users (the Kendall’s tau values ranged from 0.90 to 0.93) suggests similar needs for injury prevention. A new brain injury assessment criterion may serve all road user types.
Meng, Shiyang, Schindler, Ron, Kleiven, Svein, Lubbe, Nils
Occupant Sex Equity and Vehicle Safety: Historical Activities, Research, and Countermeasure2026-22-00025/28/2026
Since 2019, sex equity in traffic crashes has been a highly debated topic in vehicle safety, especially following the 2019 study by Forman et al. (1) claiming that female occupants face a 73 percent greater risk of serious injury in frontal crashes compared to male occupants. This was soon followed by a Consumer Reports Article by Keith Barry (2), which attempted to identify underlying factors contributing to the higher risk. These have been embraced by several parties since 2019. Firstly, it was alleged that vehicle design practice over the last four decades considered safety for the male population only and ignored that of the female as evidenced by the exclusive use of the mid-sized male Anthropomorphic Test Devices (ATDs) in Regulatory and Safety Ratings tests and not with an average sized female ATD. The absence of such an ATD for testing of vehicles “set the course for four decades’ worth of car safety design, with deadly consequences” (2). Secondly, although there is a recognition of the fact that Regulatory testing with a Small Female ATD, the Hybrid III-05F, was introduced in the FMVSS208 in 2003, this ATD was only a scaled version of the average male ATD of the 1970’s implying that this ATD is incapable of driving the design of restraint systems for females due to “They’re put together differently. Their material properties—their structure—is different” (2). Thirdly, according to a quote “These same trends have been observed in many, many studies in the past.” We assume that the trends refer to the apparent disparity in safety of females when compared to those of males. This document aims to outline historical activities, associated research and the development of countermeasures addressing crashworthiness concerns related to vehicle safety for females, as well as factors affecting both males and females, such as age-related impacts. This paper deals mainly with the frontal crash modes, mentions side impacts briefly as it affected designs of inflatable restraints for side impact to protect the smaller portion of the population from inflation induced injuries but the history behind the use of female ATDs by IIHS and NHTSA in full scale testing is not covered. Where ever possible, the time periods of reported activities related to female safety have been divided to pre-1997 corresponding to a change in US frontal crash regulation to address serious-to-fatal injuries to females and children, between 1997 to 2003 corresponding to the proposal by Canada for its frontal impact standard, and between 2003 and 2006 when the Advanced Restraint Regulation in the US FMVSS 208 was promulgated. This was followed by activities between 2007 and 2019, and post 2019 period.
Prasad, Priya, Dalmotas, Dainius J.
Research on Automatic Installation of Flash-Type Bird Collision Warning Device on Drones2026-99-17195/22/2026
Bird accidental collision with overhead transmission lines poses a threat to the ecology of rare bird populations. This article analyzes the warning measures to prevent birds from accidental collisions at home and abroad. In response to the low efficiency of manual installation and the poor static warning effect in preventing birds from accidental collisions with overhead transmission lines, the visual characteristics of birds are analyzed. A drone-based automatic installation flash-type bird accidental collision warning device is proposed, which includes a fixture, a disc, and a luminous circuit. The fixture can be carried and installed on the overhead line by a drone and can be easily disassembled. The disc adopts eye-catching colors and has a hollow structure to reduce wind resistance load. The luminous circuit includes solar panels, charge and discharge control circuits, flicker control circuits, batteries, and luminous components. The drone suspension warning device test was conducted, and the results showed that the device can be easily suspended from the overhead line by the drone.
Wang, Jian, Wang, Xiulong, Liu, Bin, Li, Danyu, Xu, Xunjian
A Real-Time Monitoring and Rapid Warning Method for Guardrail Collisions in Intelligent Transportation Systems2026-99-07235/15/2026
This article proposes a method for real-time monitoring and rapid alert for guardrail collisions based on Distributed Acoustic Sensing (DAS). The aim is to enhance traffic safety through continuous analysis of vibration signals. To achieve this, a system architecture that combines both hardware and software design has been developed, enabling the handling of the entire process from signal acquisition and decoding to intelligent event recognition and visualization. To improve signal reliability, an adaptive noise reduction algorithm and a multi-level feature extraction method are introduced, enabling accurate differentiation between collision events and environmental disturbances. Tests at various vehicle speeds show that the DAS-based system detects collisions with over 98% accuracy and cuts false alarms by more than 60% compared to traditional video and point-sensor monitoring. It can locate accidents with an average error of 4.2 meters and respond in under 1 second, demonstrating both its accuracy and speed. These results confirm the method’s effectiveness and reliability for enhancing transportation safety.
Sun, Lang
Letter from the Guest Editor09-14-01-00345/13/2026
Letter from the Guest Editor
Tylko, Suzanne
Letter from the Editor-in-Chief09-14-01-00015/13/2026
Letter from the Editor-in-Chief
Hardy, Warren N.
Applications of Multiple Spatial Audio Cues to Rotorcraft Scenarios: Too Much or Simply Misunderstood?F-0082-2026-02035/5/2026
This study evaluates the operational impact of multiple concurrent spatialized auditory cues during high-workload rotorcraft missions. A controlled, within-subject flight simulation experiment was conducted in which military-qualified rotorcraft pilots completed continuous multi-objective missions including formation flying, visual asset detection, collision avoidance, and emergency landing tasks. Each mission was flown under spatialized (3D) and non-spatialized (2D) audio rendering conditions while cue composition remained constant. Preliminary results indicate that under complex, formation-dominant workload conditions, pilots consistently prioritized visually anchored tasks and largely deprioritized auditory cue information regardless of spatial rendering. Collision avoidance cues did not produce observable evasive responses, and reported cue trust remained low without prior training. Although limited performance improvements were observed in isolated conditions, participants reported consciously suppressing audio cues. These findings suggest that effective integration of spatial audio requires structured training, procedural embedding, and deliberate workload redistribution rather than perceptual enhancement alone.
Beers, Heather, Prasad, J.V.R., Magalhaes, Jose, Bowers, Ryan, Tauro-Padival, Rahul, Feigh, Karen M.
Air Tour Helicopter Accidents (2014 to 2024): A Data-Driven Exploration of Causal and Contributing FactorsF-0082-2026-01675/5/2026
Helicopter air tours operate in one of the most challenging and least-controlled environments of commercial aviation, yet the safety outcomes of these operations remain inconsistent across regulatory frameworks. This study examined 55 helicopter air tour accidents in the United States from 2014 to 2024 using data from the NTSB Case Analysis and Reporting Online database. Defining event narratives, contributing factors narratives, and probable cause were coded to identify causal relationships between accidents and identify safety trends between 14 CFR Part 91 operations and Part 135 operations. CFR Part 91 operations exhibited accident rates approximately three times higher than Part CFR 135, averaging 3.94 per 100,000 flight hours compared to 1.23. Maintenance/mechanical was the most common initiating cause for accidents under CFR Part 91, accounting for 52% of cases compared to 37% under Part 135. Pilot/related cases were more prevalent under CFR Part 135, accounting for 53% of accidents. The two regulatory frameworks operated substantially different fleets, with CFR Part 91 relying on reciprocating-engine helicopters (76%) and Part 135 on turbine-powered aircraft (81%). Engine and powerplant/related events accounted for 27% of all defining events, and nearly half of all events involved a technical or mechanical initiator.
Sanchez, Gustavo, Gupta, Shantanu, Coimbra Mendonca, Flavio
Characterization of Lane Keeping and Departure Scenarios Using Large-Scale Naturalistic Driving Data09-14-01-00225/4/2026
Roadway departures remain a major cause of crashes, injuries, and fatalities on U.S. roads. Technologies such as lane keeping assist (LKA) and lane centering assist (LCA) can help mitigate these crashes, but their development involves extensive characterization of the parameter space in which they operate. Lane and road departures (LDs/RDs) and lane changes (LCs) must be systematically described and quantified to distinguish kinematic features, identify contributing factors, and benchmark system influence on lateral control. This study developed a unified pipeline to mine over 36 million miles of naturalistic driving study (NDS) data collected from more than 3800 participants. The pipeline integrates various types of signals to detect roadway boundary crossings, classify LKA-relevant scenarios, and extract roadway, driver, environmental, and assistance-related parameters. Lane keeping epochs with and without LKA were also extracted to quantify system influence on lateral control. In the NDS analysis, crashes include both object contact events and RDs, defined as non-premeditated departures from the intended travel surface involving at least one tire. Analysis of pre-identified crashes in the NDS showed that unintentional RDs accounted for 5.67%, unintentional LDs for 1.76%, and intentional LCs for 1.55%, corresponding to lower-bound rates of 2.7, 0.8, and 0.7 crashes per million vehicle miles traveled. RD crashes were predominantly right-sided, LD crashes left-sided, and both were overrepresented on curves and under adverse conditions. Loss of control preceded 22% of RD crashes and 69% of LD crashes. Beyond crashes and near-crashes (CNCs), the algorithm identified approximately 3 million LCs and 0.3 million LDs/RDs. LCs typically involved larger crossing angles that decreased with speed, while departures clustered within 0°–2°. Compared with CNCs, these occurred at higher speeds and smaller angles. LKA consistently reduced lateral variability without biasing the mean offset.
Ali, Gibran, Terranova, Paolo, Williams, Vicki, Holley, Dustin, Saffy, Joshua, Antona-Makoshi, Jacobo, Kefauver, Kevin, Shull, Emily, Li, Eric, Venegas, Michael
Advanced Tool for Traffic Crash Analysis: An AI-Driven Multi-Agent Approach to Pre-Crash Reconstruction09-14-01-00335/4/2026
Traffic collision reconstruction traditionally relies on human expertise and, when performed properly, can be incredibly accurate. However, attempting to perform pre-crash reconstruction, i.e., reconstructing the driver and vehicle behaviors that preceded the actual crash, poses significantly more challenges. This study develops a multi-agent artificial intelligence (AI) framework that reconstructs pre-crash scenarios and infers vehicle behaviors from fragmented collision data. We present a two-phase collaborative framework combining reconstruction and reasoning phases. The system processes 277 rear-end lead vehicle deceleration (LVD) collisions from the Crash Investigation Sampling System (CISS; 2017–2022), integrating textual crash reports, structured tabular data, and visual scene diagrams. Phase I generates natural language crash reconstructions from multimodal inputs. Phase II performs in-depth crash reasoning by combining these reconstructions with the temporal event data recorder (EDR). This enables precise identification of striking and struck vehicles while isolating the EDR records most relevant to the collision moment, thereby revealing crucial pre-crash driving behaviors. For validation, we applied it to all LVD cases, focusing on a subset of 39 complicated EDR cases where multiple EDR records per collision introduced possible ambiguity (e.g., due to missing or conflicting data). Ground truth was established via consensus between manual annotations (two independent researchers), with a separate large language model (LLM) used only to flag possible conflicts for re-checking. In the full end-to-end evaluation, the framework achieved 100% accuracy across all 4155 trials (277 cases × 5 runs × 3 models), with three reasoning models producing identical outputs, confirming that performance derives from the structured prompt design rather than model-specific characteristics. In contrast, research analysts without specialized reconstruction training achieved 92.31% accuracy on the same 39 complex cases. In separate ablation experiments on the 39 complicated EDR cases, where one randomly selected Phase I output from the full end-to-end evaluation was fixed as the unified input for Phase II and each model was tested with 10 independent runs, removing the structured reasoning anchors reduced case-level accuracy from 99.7% to 96.5%, with errors spreading from a single output type to multiple analytical dimensions. The system maintained robust performance even when processing incomplete data. This zero-shot evaluation, conducted without any domain-specific training or fine-tuning, demonstrates that the framework’s effectiveness stems from its multi-agent architecture and prompt engineering, offering a scalable approach for AI-assisted pre-crash analysis.
Xu, Gerui, Chen, Boyou, Guo, Huizhong, LeBlanc, Dave, Kusari, Arpan, Yarbasi, Efe, Ahmed, Ananna, Sun, Zhaonan, Bao, Shan
SAE Level 2 ADAS Performance in Specific Crash-Imminent Scenarios09-14-01-00155/4/2026
This research examined the performance of SAE Level 2 (L2) advanced driver assistance systems (ADAS) in crash-imminent scenarios (CIS), with particular attention to how vehicle configuration like body style and powertrain (internal combustion engine, plug-in hybrid, electric vehicle) influences vehicle system performance. The objectives were to (1) identify CIS relevant to L2-equipped vehicles using crash databases and naturalistic driving studies (NDSs), (2) develop scenario-based test procedures and test matrices, and (3) evaluate system and vehicle responses across configurations and conditions. Multiple crash data sources were analyzed, including NHTSA’s Standing General Order dataset of L2-related crashes, the Fatality Analysis Reporting System, the Crash Report Sampling System, and NDS data from the Second Strategic Highway Research Program and the Virginia Tech Transportation Institute L2 NDS. Coded variable analyses from the datasets identified three common CIS: lane and road departures, rear-end striking events, and intersection conflicts. Supporting variables such as speed, roadway condition, and driver actions were also extracted to characterize scenarios and inform test development. Tests were executed at a closed-track testing facility using four vehicles selected for diversity of L2 systems, body types, and powertrains. Phase 0 exploratory testing assessed vehicle kinematics and L2 responses to refine the test matrix. Phases 1 and 2 conducted controlled evaluations of selected CIS, with expansion factors reflecting real-world crash variability. The testing highlighted interactions between L2 features and active safety systems. For example, results showed that all four vehicles employed distinct hand-off strategies between L2 longitudinal control and active safety systems during rear-end striking crash scenarios, and AEB engagement was strongly correlated with TTC at the moment the vehicle identified the crash partner. This work contributes novel insights into vehicle L2 and ADAS behavior in CIS events across multiple factors and provides a structured framework to evaluate system behavior for those crash-imminent scenarios.
Beale, Gregory, Kefauver, Kevin, Venegas, Michael, Li, Eric, Chen, Jay, Huggins, Steven, Guduri, Balachandar, Llaneras, Eddy
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