Flight Crew Research Articles

A Machine Learning-Based Model for Flight Turbulence Identification Using LiDAR Data

By addressing the imbalanced proportions of the data category samples in the velocity structure function of the LiDAR turbulence identification model, we propose a flight turbulence identification model utilizing both a conditional generative adversarial network (CGAN) and extreme gradient boosting (XGBoost). This model can fully learn small- and medium-sized turbulence samples, reduce the false alarm rate, improve robustness, and maintain model stability. Model training involves constructing a balanced dataset by generating samples that conform to the original data distribution via the CGAN. Subsequently, the XGBoost model is iteratively trained on the sample set to obtain the flight turbulence classification level. Experiments show that the turbulence recognition accuracy achieved on the CGAN-generated augmented sample set improves by 15%. Additionally, when incorporating LiDAR-obtained wind field data, the performance of the XGBoost model surpasses that of traditional classification algorithms such as K-nearest neighbours, support vector machines, and random forests by 14%, 8%, and 5%, respectively, affirming the excellence of the model for turbulence classification. Moreover, a comparative analysis conducted on a Zhongchuan Airport flight crew report showed that the model achieved a 78% turbulence identification accuracy, indicating enhanced recognition ability under data-imbalanced conditions. In conclusion, our CGAN/XGBoost model effectively addresses the proportion imbalance issue.

Robust fault detection and diagnosis of primary air data sensors in the presence of atmospheric turbulence

Abstract This paper presents a fault detection and diagnosis (FDD) algorithm for various faults in the primary air data sensors (PADS) of an aircraft in the presence of external disturbances such as atmospheric turbulence. Rapid wind variations due to turbulence induce excessive error in the externally fitted air data probe measurements, which may lead to loss of control and misinterpretations by the flight crew. In adverse environmental conditions, the FDD of air data prefers robust and adaptive air data estimates that use an analytical redundancy approach with fewer computations. The proposed method considers the kinematics of the aircraft instead of the dynamics used in the state-of-the-art algorithms. The advantage of using kinematics is that it can reduce modeling errors significantly, avoiding high false alarm rates in the FDD process. For the estimation of stable and accurate air data under external disturbance, the inertial navigation system and global positioning system (INS/GPS) output are considered instead of actual air data probe or sensor measurements. The proposed algorithm uses estimates of air data using an exponentially weighted adaptive extended Kalman filter (EW-AEKF) to detect and diagnose PADS faults, which can perform well even in the presence of uncertain noise due to atmospheric turbulence experienced during flight. The simulation was carried out to validate the algorithm with flight data obtained from the X-Plane flight simulator under moderate atmospheric turbulence. The simulation experiments were carried out using the MATLAB programming platform. The results show that the proposed method achieves satisfactory FDD performance with lower root mean square error (RMSE) and computation time than traditional EKF-based algorithms.

Pilot Selection in the Era of Virtual Reality: Algorithms for Accurate and Interpretable Machine Learning Models

With the rapid growth of the aviation industry, there is a need for a large number of flight crew. How to select suitable prospective pilots in a cost-efficient manner has become an important research question. In the current study, 23 pilots were recruited from China Eastern Airlines, and 23 novices were from the community of Tsinghua University. A novel approach incorporating machine learning and virtual reality technology was applied to distinguish features between these participants with different flight skills. Results indicate that SVM with the MIC feature selection method consistently achieved the highest prediction performance on all metrics with an accuracy of 0.93, an AUC of 0.96, and an F1 of 0.93, which outperforms four other classifier algorithms and two other feature selection methods. From the perspective of feature selection methods, the MIC method can select features with a nonlinear relationship to sampling labels instead of a simple filter-out. Our new implementation of the SVM + MIC algorithm outperforms all existing pilot selection algorithms and perhaps provides the first implementation based on eye tracking and flight dynamics data. This study’s VR simulation platforms and algorithms can be used for pilot selection, training, and personnel selection in other fields (e.g., astronauts).

Analysis of Single-Pilot Intention Modeling in Commercial Aviation

With the continual enhancement of the onboard avionics, the minimum flight crew has been downsized from five to two-person crew mode, and reduced crew operation has drawn extensive attention from aviation experts. Single-pilot operation (SPO) mode warrants careful account and research. This study investigated the intention modeling of commercial aviation single pilot based on the bidirectional long short-term memory (BiLSTM), mining the intention tendency of pilots’ behavior through artificial intelligence technology. This was done to avoid safety hazards caused by different intents and inconsistent operations of the single pilot and the cockpit automation system. The classification task of a single pilot’s behavior is the core of intention recognition. Various operation items contribute differently to the classification. To construct the interaction dataset and encode it into time series features, a single-pilot experiment is specifically performed, wherein the experience of an expert is summarized into single-pilot intent labels. The deep information in the feature vector of a single-pilot operation item is captured by the BiLSTM network, and the neural weight is adaptively assigned by the training mechanism. The operation sequence with the feature data is finally loaded into the softmax layer for intention classification. The proposed method is evaluated against long short-term memory (LSTM), term frequency-inverse document frequency (TF-IDF), convolutional neural network (CNN), Naive Bayesian (NB), and distributed representation’s intention modeling techniques. Because the proposed methods have higher F1 scores, the model can effectively share real-time information about the single-pilot intention with the cockpit automation system.

Study of the feeding performance of mesoporous silica in a loss-in-weight feeder

Accurate and reliable continuous feeding is essential for the continuous manufacturing of solid-dose pharmaceuticals to ensure the reproducible composition of the final product. Consistent feeding of cohesive powders is challenging and requires an understanding of the interplay between material properties and feeder configuration. This study presents the volumetric and gravimetric feeding behaviour of a cohesive pharmaceutical, excipient mesoporous silica, at low feed rates (< 0.6 kg/h) using a twin-screw loss-in-weight feeder. The study investigates how the screw pitch, screen type and gravimetric setpoint impact the feed factor and feed rate variability. Additionally, the flow function and bulk density of the fed and unfed silica samples were determined and related to the feeding process parameters. Volumetric experiments highlight inconsistent feed due to the poor screw flight filling at high screw speeds and for configurations with the larger pitch, coarse concave screw. Poor screw flight filling also resulted in an inverse relationship between screw speed and feed factor in volumetric mode. In gravimetric mode, feed variability, expressed as %RSD, was greatest at the lower gravimetric setpoints with minimal impact due to tooling configuration. Discharge screen set-up was identified as the parameter which had a significant effect on the bulk density and flowability of the powder post-feeding.

Southwest's holiday troubles offer lessons for nonprofits

Over the recent holiday season, anyone traveling by plane—and even those not traveling—likely heard about the widespread flight delays that impacted thousands of people across the country. The issue came to forefront when Southwest Airlines had to cancel thousands of flights, seemingly due to bad weather. But as it turns out, the true culprit for the cancellations was actually outdated technology the company used for reassigning flight crews, which was unable to keep up with the surge in demand that was, initially at least, spurred by winter weather events.

Nonprofits can draw valuable lessons from Southwest's holiday troubles

Over the 2022 holiday season, flight delays across the country made headlines, with one company perhaps vilified more than others—Southwest. The company experienced widespread flight delays, impacting thousands of people across the country during critical holiday travel, seemingly due to bad weather. But as it turns out, the true cause for the cancellations was actually outdated technology the company used for reassigning flight crews, which was unable to keep up with the surge in demand that was, initially at least, spurred by winter weather events.

SYNBIO® Probiotic and Antioxidant Dietary Supplementation: Clinical Trial Evaluation of Potential Effects on Airline Flight Crew Members' Well-Being.

The irregular lifestyle of airline crew members, wide/adverse job-related exposures, and the impact of temporary hypoxia on gut microbiota well-being have increased concern about the daily recommended dose of certain nutrients among flight crew. The aim of this study was to determine if daily consumption of a SYNBIO® probiotics-elderberry extract supplement (ACTIVE) may contribute to the well-being of flight attendants. Forty healthy crew members enrolled in a double-blind, randomized, placebo-controlled study consumed one ACTIVE capsule/day or placebo for 30 days. Bowel well-being, health-related quality of life, and gastrointestinal tolerance were assessed by validated questionnaires. Saliva and fecal samples were analyzed to determine secretory immunoglobulin-A (sIgA) levels and to characterize gut microbiota composition, respectively. ACTIVE subjects presented a physiological improvement and a statistically significant higher Psychological General Well-Being Index (PGWBI) global score compared to PLACEBO subjects. The ACTIVE subjects showed significantly increased levels of lactobacilli and bifidobacteria compared to the PLACEBO group, while a significant increase in lactobacilli and a significant reduction in Enterobacteriaceae were registered when compared with the beginning of supplementation, confirming the persistence of probiotics in the gastrointestinal tract and the direct antagonism and competitive exclusion effects. Additionally, sIgA levels were significantly higher in the ACTIVE group compared to the baseline and to the PLACEBO group at the end of supplementation. The ACTIVE supplementation might be beneficial to airline crew members, improving their physiological state, their immune defenses, and the strength and efficiency of their gastrointestinal tract when responding to stressful conditions.

The development of the helicopter non-technical skills (HeliNOTS) behavioural marker systems

Behavioural marker systems (observational frameworks geared towards the assessment of non-technical skills by way of behavioural markers) exist across a variety of high-risk occupations, however, no identifiable system currently exists developed from rotary operative data. In this study, discussion groups (n = 9) were undertaken with subject matter experts (n = 20)—including pilots and technical crew operating across search and rescue and offshore transport environments—with the objective of identifying role-specific behavioural markers. Systems were reviewed on an iterative basis by the academic team and received final reviews by additional subject matter experts (n = 6). Two behavioural marker systems were constructed: HeliNOTS (O) for offshore transport pilots and HeliNOTS (SAR) for search and rescue crews; each with domain-specific behavioural markers. Both represent a significant step towards a nuanced approach to training and assessment of helicopter flight crews’ non-technical skills and are the first publicly available systems tailored to these distinct mission types. Practitioner summary: There is no publicly available behavioural marker system based on data from rotary operatives. Across this study, two prototype systems were developed: HeliNOTS (SAR) for helicopter search and rescue, and HeliNOTS (O) for helicopter offshore transport. Both HeliNOTS systems represent a nuanced approach towards rotary CRM training and assessment.

Why Are Flight Psychologists Important to Flight Safety?

The developments in aircraft technologies both in our country and around the world cause a serious increase in both the aircraft fleets and ticket sales, as well as the number of airline companies, their employees and passengers. These developments in the aviation industry necessitate flight safety and highlight the importance of the human factor (flight crew) by reducing the causality of technical factors in ensuring safety. Studies within this scope show that the main causal factor (65-70%) in aircraft crashes is the flight crew. There are many factors such as physiological, psychological, personal and psychosocial at the basis of the unsuccessful performance of the flight crew. However, the number of studies in the literature that draw attention to the psychological elements of the flight crew is very few. In fact, it is known that the psychological well-being of the flight crew is important for the success of the flight operations, but the airline companies do not have any evaluation obligation regarding this. On the contrary, some negative consequences may be encountered due to the freedom in this matter. In particular, the fact that human factor causation is at a much higher level than previously thought in plane crashes increases the importance of flight psychologists for airline companies today. Therefore, in this study, it is aimed to reveal the importance of flight psychologists on flight safety in civil aviation. In this context, interviews were held with the flight crews of two airlines (private-public). The findings show that flight psychologists are important and necessary in airline companies in order to be able to perform safe flights with healthier flight crews.

UPLC-MS/MS simultaneous quantification of urinary circadian rhythm hormones and related metabolites: Application to air traffic controllers

Civil aviation flight crew and civil aviation air traffic controllers are prone to circadian rhythm abnormalities, which can lead to a slew of other maladies. It could endanger people's health and provide a serious threat to the safety of civil aviation flights if it is not appropriately evaluated and addressed. Early detection of rhythm irregularities and prompt treatment for particular populations that are vulnerable to rhythm disorders are crucial for enhancing civil aviation safety.In general, monitoring of the classical circadian rhythm biomarkers (melatonin or cortisol) in plasma or saliva is an effective way to evaluate the rhythm status. Due to the challenging sample procedure and the trauma of plasma, urine sample testing has received an increasing amount of attention. While, urine circadian rhythm biomarkers have seldom been examined, and the relationship between urinary steroid hormones and melatonin is still poorly understood. In most cases, hormones are determined by immunoassays respectively, mainly enzyme-linked immunosorbent assay (ELISA) or radioimmunoassay (RIA). There are also reports describing the liquid chromatography with tandem mass spectrometry (LC-MS/MS) technique as a method of melatonin or few steroid hormones quantification, however, the simultaneous detection of multiple rhythmic hormones in human urine is rarely reported.For the quantification of the rhythmic hormones in human urine, an accurate approach using ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was devised in this work. Nine endogenous hormones (melatonin, 6-hydroxymelatonin, 6-sulfatoxymelatonin, cortisol, corticosterone, cortisone, testosterone, epitestosterone and androsterone), in human overnight urine, were quantified after solid phase extraction (SPE). A reverse phase HSS C18 column was used for chromatographic separation with a 9-minute gradient elution and deuterated analogues of each analyte were applied as internal standards. This method was successfully applied to the analysis of 596 overnight urine samples (23:00–9:00) collected from 84 air traffic controllers in the Beijing area during shift work. This study's findings showed a clear correlation not only between melatonin and its metabolites; cortisol-related metabolites, but also between melatonin metabolites and endogenous metabolites upstream and downstream of cortisol, implying that these two categories of hormones can be used as potential biological rhythm indicators to provide circadian rhythm data support for future studies on circadian rhythm disorders.

Improved space weather observations and modeling for aviation radiation

In recent years there has been a growing interest from the aviation community for space weather radiation forecasts tailored to the needs of the aviation industry. In 2019 several space weather centers began issuing advisories for the International Civil Aviation Organization alerting users to enhancements in the radiation environment at aviation flight levels. Due to a lack of routine observations, radiation modeling is required to specify the dose rates experienced by flight crew and passengers. While mature models exist, support for key observational inputs and further modeling advancements are needed. Observational inputs required from the ground-based neutron monitor network must be financially supported for research studies and operations to ensure real-time data is available for forecast operations and actionable end user decision making. An improved understanding of the geomagnetic field is required to reduce dose rate uncertainties in regions close to the open/closed geomagnetic field boundary, important for flights such as those between the continental US and Europe which operate in this region. Airborne radiation measurements, which are crucial for model validation and improvement, are lacking, particularly during solar energetic particle events. New measurement campaigns must be carried out to ensure progress and in situ atmospheric radiation measurements made available for real-time situational awareness. Furthermore, solar energetic particle forecasting must be improved to move aviation radiation nowcasts to forecasts in order to meet customer requirements for longer lead times for planning and mitigation.

Moral values of a future military pilot as the reliability of predicted professional psychological selection

Abstract. Aim. To identify one of the problems of professional psychological selection of applicants for training in a higher military flight school, to show the importance of moral values in the professional development of a military pilot and the impact of their presence or absence on the quality of the prediction as part of professional psychological selection. At present, the progress and constant modernisation of the Russian Air Force aircraft fleet places ever higher demands on the level of professionalism of a modern military pilot. In this context, there is a growing need for greater numbers of indicators diagnosed during professional psychological selection (PPS) that are later used to predict the success of military flight training and professional activity in general. That is primarily due to the fact that recently more and more attention has been paid to the role of the personality and its integrative function. However, at present, the existing flight crew PPS system does not provide a comprehensive diagnosis of a candidate’s personality.Methods. Based on a theoretical analysis of the work conducted by researchers and practitioners of aviation psychology and various approaches to the study of the professional fitness of flight personnel, it was identified that the key element in the diagnosis of professional fitness is the personality with its integrative function and the whole set of professionally important qualities. The analysis of literature in aviation psychology shows that personal qualities determine motivation, focus and sustained interest in flight work, as well as the social type of behaviour and a person’s adaptation to specific conditions of flight activity and military service.Results. A pilot’s professionalism begins with shaping the personality. Nowadays, the loss of spiritual guidelines has led to a dramatic simplification of moral values and patriotic spirit, and young people are more focused on consumerism. Selecting candidates for military aviation involves the use of a diverse set of diagnostic techniques that helps evaluate the most important psychological and personal qualities. However, the experience of application of personal questionnaires shows that they do not always represent a complete picture of an applicant’s motivation, personality orientation, self-awareness and basic values. The use of projective and hardware-based methods is minimised, the existing automated system for professional psychological selection (ASPPS) is insufficiently equipped with methods that diagnose personal qualities, the emphasis being placed on diagnosing cognitive processes. The century-old history of PPS shows a violation of the principle of personal integrity, which isexpressed in the bias towards psychophysiology. As a result, at present, the existing flight crew PPS does not provide a comprehensive diagnosis of a candidate’s personality.Conclusions. In conclusion, it is noted that the key element in the diagnosis of professional aptitude is the personality with all its PIQ and moral values. Growing numbers of diagnosed indicators in the personal block of the PIQ will enable a comprehensive diagnosis of a candidate, and thanks to a combination of survey and projective methods, it will help increase the reliability of the PPS prediction, provided that an applicant’s personality is treated holistically, based on the principles of an integrative approach to the person as an integral personality.

Development of a theoretical model of pilot decision making with conflicting information

AbstractThe advancement of technology on the modern commercial flight deck has allowed flight crew members to utilise multiple sources of information to maintain the safety of their flight. Having multiple sources of flight deck information, capable of displaying the same type of information, can lead to a situation in which a pilot encounters conflicting information. Understanding how a pilot makes a decision when faced with an information conflict on the flight deck is important to ensure appropriate design of flight-deck information systems and effective pilot training. This effort utilised data collected from 25 airline pilots who experienced information conflicts on a simulated B-737 flight deck, in conjunction with a theoretical review of how information conflicts impact decision making, to develop a theoretical model of pilot decision-making in the presence of an information conflict. This manuscript describes the model, along with the theory-driven and data-driven approaches utilised to develop the model.

Air Medical Support for a Peripheral Hospital in Southern Israel: An Evolving Role for the Air Ambulance and Emergency Department Clinicians

The early use of helicopters on the battlefields of Korea and Vietnam led to the introduction of “air ambulances” into civilian practice. Initially, these aircraft were tasked to retrieve casualties and provide conventional paramedic care at the scene and en route to the hospital. The introduction of advanced medical teams on helicopters led to the evolution of helicopter emergency medical service units. Yoseftal Hospital is a 65-bed hospital serving the town of Eilat in southern Israel. It does not offer full intensive care or specialist services but does provide general surgical, medical, pediatric, and psychiatric services. The hospital is 100 km from the nearest tertiary center in Be'er Sheva, an ambulance journey of 2 hours across desert. The hospital serves a population of 70,000 residents and up to 500,000 tourists. Recognizing the need to provide a facility to transfer critical or complex patients, in August 2021, the Israeli Ministry of Health provided a dedicated helicopter to Yoseftal Hospital. The first 100 missions are presented. Forty-four missions were for cardiac presentations. For patients with ST-segment elevation myocardial infarction, the median time from the initial medical contact at Yoseftal to reception at the tertiary center was 141 minutes. Other transfers were for ear, nose, and throat (2); neurosurgical (14); trauma (9); respiratory (6); obstetrics and gynecology (3); and pediatric services (14) and nontraumatic surgical emergencies (15). Our experience validates the need for this resource and highlights the importance of robust clinical, operational, and transfer protocols between Yoseftal and the receiving specialist units. The challenging and diverse clinical activity requires additional skills and competencies for the critical care paramedics on the aircraft. Integrating the flight crew into the emergency department team facilitated early activation of the aircraft and expedited patient preparation for flight. Our experience describes an evolving new role for the helicopter—support for a remote peripheral hospital.

TO FLY THE PLANE: LANGUAGE GAMES, HISTORICAL NARRATIVES, AND EMOTIONS

The common Western distinction between reason and emotion (which is not found outside Western-influenced traditions) tends to obscure an important distinction between two kinds of thinking: logical and mathematical reasoning, on the one hand, and, on the other hand, what is sometimes called “situational awareness,” a kind of thinking that involves striving to take into account multiple simultaneously true descriptions of a situation. Emotion, as understood in appraisal theory (that is, as inherently cognitive and intentional), is one kind of thinking that contributes to—indeed, is crucial to—situational awareness in this sense. Intention also belongs to situational awareness. Whatever long-term goals we pursue, present action must be attuned to immediate circumstances. One is faced with an indefinite number of ways to describe what is going on at any moment, and this second kind of thinking involves striving to identify a crucial subset of these true descriptions that one can respond to via an intentional action, procedure, or plan. Maintaining situational awareness in this sense is the goal of “crew resource management” (CRM), a flight crew teamwork strategy and emotional regime aimed at ensuring airline safety. The philosophical works of Wittgenstein, Anscombe, Austin, Habermas, and Danto, among others, help explain the remarkable successes of crew resource management. This article tests this explanation's applicability to nonmodern contexts by briefly discussing the letters of Antoine de Bourbon and Jeanne d'Albret between 1551 and 1562.

The Royal Flying Doctor Service Initiation of Helicopter Video Simulation Orientation Training for Air Medical Crews in Western Australia: A Pilot Study

ObjectiveIn May 2022, the Royal Flying Doctor Service Western Operations in Western Australia pioneered the introduction of the first organizational helicopter emergency service with 2 Eurocopter EC145 helicopters. This article describes the pilot study undertaken, assessing the implementation and flight crew confidence outcomes of the supplementation of video simulation training to standard clinical training for helicopter air medical retrieval. MethodsSurvey assessments using a 5-point Likert scale provided anonymous demographic data with summarized results of the means and standard deviations. Nonparametric tests were used to compare responses between the control and experimental groups from pretraining to postintervention to postpractical. ResultsThe findings showed an increase in confidence rates after a classroom session and further increases after a practical session in the control group. The intervention group showed a small rise in overall confidence levels after being shown video simulations following the completion of their classroom session before commencing their practical session. This study established that regardless of the airframe, clinical staff, often with significant experience in air medical retrieval and critical care medicine, do not automatically have confidence in performing critical care procedures in a new aircraft type to which they have not previously been oriented. The results display a statistically significant increase in confidence levels in procedural performance after the classroom session compared with the pretraining questionnaire, with a subtle further rise when video simulations are included in the classroom session. When a classroom session is subsequently supplemented with a practical simulation session, confidence levels continue to rise. ConclusionImplementing a comprehensive educational strategy including classroom and practical elements for clinical staff in their orientation to new aircraft improves their confidence in performing critical care procedures if required in flight. The addition of in-flight prerecorded videos demonstrating these critical care procedures is a useful adjunct to simulation training for flight crew in air medical retrieval, and further analytical studies may indeed show a statistically significant improvement in staff confidence.

An intelligent approach for flight risk prediction under icing conditions

Flight risk prediction is significant in improving the flight crew's situational awareness because it allows them to adopt appropriate operation strategies to prevent risk expansion caused by abnormal conditions, especially aircraft icing conditions. The flight risk space representing the nonlinear mapping relations between risk degree and the three-dimensional commanded vector (commanded airspeed, commanded bank angle, and commanded vertical velocity) is developed to provide the crew with practical risk information. However, the construction of flight risk space by means of computational flight dynamics suffers from certain defects, including slow computing speed. Accordingly, an intelligent approach for flight risk prediction is proposed to address these defects based on neural networks. Radial Basis Function Neural Network (RBFNN) is optimized using Adaptive Particle Swarm Optimization (APSO). To optimize both the parameters and the structure of APSO-RBFNN, a fitness function containing the training accuracy and network structure size is proposed. Extensive experimental results demonstrate that the flight risk predicted by APSO-RBFNN is very close to that obtained via computational flight dynamics. The average error (RMSE) is less than 10-1. The approach achieves a speedup close to 1000x compared with computational flight dynamics. In addition, some flight upset and recovery cases are presented to illustrate the efficiency of the intelligent approach for flight risk prediction.

Downsizing the jet: A forecast of economic effects of increased automation in aviation

We develop a theory of optimal aircraft size, where the cost of the flight crew is the primary factor driving the use of larger aircraft, while passenger utility is primary factor driving the use of smaller aircraft. After fitting our model to U.S. data, we perform a counterfactual experiment where the minimum crew size requirement is relaxed from two pilots to one, a policy currently being discussed by aviation experts. Implications are derived for the number of aircraft demanded and its size distribution, demand for pilots, passenger traffic, flight frequency, and where new nonstop service may be introduced.

Abstract TMP46: Large Vessel Occlusion Stroke Knowledge And Clinical Training In Emergency Medical Service Personnel In The United States

Background: Stroke education of emergency medical service (EMS) personnel improves stroke recognition, prenotification, and thrombolytic delivery. Prehospital identification of large vessel occlusion (LVO) stroke may facilitate the creation of a regional bypass protocol and improvement of intrahospital and interhospital workflows. However, the current status of EMS personnel’s knowledge of LVO, their stroke severity assessment training, and preferences in educational methods have not been studied. We conducted an EMS survey across the United States. Methods: The Society of Vascular and Interventional Neurology (SVIN) in collaboration with EMS-World created an online questionnaire distributed to all subscribers of EMS-World involved in pre-hospital work. It included 12 multiple-choice questions to test participants on LVO knowledge, stroke center certification levels, prior LVO education, and preferences on educational content delivery. Results: The survey email was opened by 1830 subscribers out of whom 1107 (60%) completed the survey across 50 states in the United States. Respondents identified themselves as paramedics/EMTs (91.4%), ground critical care (5.7%) and flight crew (2.9%). The number of stroke patients that survey participants transported in the past year was &lt;10 for 618 (55.8%), 10 to 25 for 332 (30%), and &gt;25 (14.2%). Two hundred eighty-five (25.8%) participants answered both LVO knowledge questions correctly and 379 (34.2%) answered one correctly. Only 128 (11.6%) correctly identified all types of centers with thrombectomy capability. Although 877 (79.2%) were familiar with at least one stroke severity scale, 376 (34%) denied receiving training to perform them. Five sixty-seven (51.2%) respondents preferred in-person training for LVO training and 429 (38.8%) an online training program. About half of all respondents (535,48%) picked 'lack of standardized LVO training' as the greatest hurdle to pre-hospital LVO management. Conclusion: EMS providers in the United States reported inadequate LVO training and demonstrated gaps in knowledge of LVO, stroke severity scales, and stroke center levels. Systematic efforts to enhance and standardize the educational content and delivery of LVO education are urgently needed.