Pilot performance and workload whilst using an angle of attack system.

Loss of control in flight is the primary category of fatal accidents within all sectors of aviation and failure to maintain adequate airspeed - leading to a stall - is often cited as a causal factor. Stalls occur when the critical angle of the aircraft is exceeded for a given airspeed. Using airspeed as an indicator of the potential to stall is an unreliable proxy. Systems that measure the angle of attack have been routinely used by military aircraft for over 50 years however rigorous academic research with respect to their effectiveness has been limited. Using a fixed-base flight simulator fitted with a simulated, commercially available angle of attack system, 20 pilots performed normal and emergency procedures during the circuit/pattern in a light aircraft. Experimental results have shown that pilot performance was improved when angle of attack was displayed in the cockpit for normal and emergency procedures during the approach phase of flight in the pattern/circuit. In relation to pilot workload, results indicated that during the approach phase of flight, there was a moderate but tolerable increase in pilot workload. The use of such a display may assist pilots to maintain the aircraft within the optimum range and hence reduce occurrences of unstable approaches. Overall, fewer stall events were observed when angle of attack was displayed and appropriate pilot decisions made during emergencies. These results provide a new perspective on pilot workload and aviation safety.

Evaluation of the impact of Covid-19 on air traffic volume in Turkish airspace using artificial neural networks and time series.

In early 2020, the aviation sector was one of the business lines adversely affected by the Covid 19 outbreak that affected the whole world. As a result, some countries imposed travel restrictions. Following these restrictions, air traffic density has decreased significantly worldwide. Since air traffic density directly affects almost all operations in air transportation, analyzing these data is very essential. For this purpose, SARIMA models, one of the linear time series models, and multilayer perceptron model (MLP), one of the artificial neural network methods suitable for nonlinear modeling, were applied to the air traffic data regarding Turkish airspace between 2010 and 2019, and the actual air traffic density was compared with the forecasts obtained from these analyses. It is considered that the results of this study are essential for organizations conducting aviation operations to take into consideration while doing future planning.

Targeted Use of Sustainable Aviation Fuel to Maximize Climate Benefits.

Sustainable aviation fuel (SAF) can reduce aviation's CO2 and non-CO2 impacts. We quantify the change in contrail properties and climate forcing in the North Atlantic resulting from different blending ratios of SAF and demonstrate that intelligently allocating the limited SAF supply could multiply its overall climate benefit by factors of 9-15. A fleetwide adoption of 100% SAF increases contrail occurrence (+5%), but lower nonvolatile particle emissions (-52%) reduce the annual mean contrail net radiative forcing (-44%), adding to climate gains from reduced life cycle CO2 emissions. However, in the short term, SAF supply will be constrained. SAF blended at a 1% ratio and uniformly distributed to all transatlantic flights would reduce both the annual contrail energy forcing (EFcontrail) and the total energy forcing (EFtotal, contrails + change in CO2 life cycle emissions) by ∼0.6%. Instead, targeting the same quantity of SAF at a 50% blend ratio to ∼2% of flights responsible for the most highly warming contrails reduces EFcontrail and EFtotal by ∼10 and ∼6%, respectively. Acknowledging forecasting uncertainties, SAF blended at lower ratios (10%) and distributed to more flights (∼9%) still reduces EFcontrail (∼5%) and EFtotal (∼3%). Both strategies deploy SAF on flights with engine particle emissions exceeding 1012 m-1, at night-time, and in winter.

Learning Assurance Analysis for Further Certification Process of Machine Learning Techniques: Case-Study Air Traffic Conflict Detection Predictor.

Designing and developing artificial intelligence (AI)-based systems that can be trusted justifiably is one of the main issues aviation must face in the coming years. European Union Aviation Safety Agency (EASA) has developed a user guide that could be potentially transformed as means of compliance for future AI-based regulation. Designers and developers must understand how the learning assurance process of any machine learning (ML) model impacts trust. ML is a narrow branch of AI that uses statistical models to perform predictions. This work deals with the learning assurance process for ML-based systems in the field of air traffic control. A conflict detection tool has been developed to identify separation infringements among aircraft pairs, and the ML algorithm used for classification and regression was extreme gradient boosting. This paper analyses the validity and adaptability of EASA W-shaped methodology for ML-based systems. The results have identified the lack of the EASA W-shaped methodology in time-dependent analysis, by showing how time can impact ML algorithms designed in the case where no time requirements are considered. Another meaningful conclusion is, for systems that depend highly on when the prediction is made, classification and regression metrics cannot be one-size-fits-all because they vary over time.

A new approach to manipulating aviator workload: A case for individualizing workload manipulations.

The present study sought to manipulate workload individually for participants to evaluate whether individual manipulations of workload produces similar subjective ratings and performance changes across participants. Participants included eight Army-rated rotary-wing aviators who presented to the laboratory for two separate visits. During the first visit, individual responses to workload were determined, and during the second visit, individually manipulated high workload flights were completed. Outcome measures included flight performance and subjective workload ratings. Data were examined at the group and individual level. Subjective ratings of workload endorsed the individual workload manipulations, while performance data provided some additional support. By taking an individualized approach such as this, researchers and practitioners may be better able to control for individual differences influencing workload. This has important implications for system design and testing, development of new intervention technologies, and assessing methods for operator monitoring.

An en route capacity optimization model based on air traffic control process.

In order to resolve the imbalance of demand-capacity and airspace congestion, improve the performance of the en route air traffic management, promote the development of air traffic control automation system in the future, this paper proposes an En route air traffic control process model from the perspective of operation requirements. Taking the minimization of operation time, instantaneous density, maximum lateral displacement and air traffic controllers' workload as the optimization objectives, the commonly used air traffic control instructions such as climb and descent and speed restriction are set as constraints, the algorithm is designed based on the air traffic control scheme, and a complete air traffic control process are modeled which outputs instructions for each aircraft. Finally, the model is applied to a case study in the northwest region of China. The simulation results show that compared with the actual operation process, the total operation time is reduced by 18.6%, the variance of the lateral displacement and the vertical separation are efficiently reduced, and the en route air traffic capacity is improved. The proposed model envisages the following two innovations: (ⅰ) the whole process of air traffic controllers' command is considered in the model, especially the control scheme and different types of instructions, and (ⅱ) the en route historical trajectory data of aircraft is used to as the key parameters of the input data to efficiently yield the acceptable results of the model. By quantifying the operation requirements of air traffic control, this model can also balance the distribution of traffic flow density, reduce the utilization rate of horizontal airspace, alleviate flight conflicts on air routes, and lessen the workload of controllers.

Absence of Pilot Monitoring Affects Scanning Behavior of Pilot Flying: Implications for the Design of Single-Pilot Cockpits.

OBJECTIVE: This study examines whether the pilot flying's (PF) scanning behavior is affected by the absence of the pilot monitoring (PM) and aims at deriving implications for the design of single-pilot cockpits for commercial aviation. BACKGROUND: Due to technological progress, a crew reduction from two-crew to single-pilot operations (SPO) might be feasible. This requires a redesign of the cockpit to support the pilot adequately, especially during high workload phases such as approach and landing. In these phases, the continuous scanning of flight parameters is of particular importance. METHOD: Experienced pilots flew various approach and landing scenarios with or without the support of the PM in a fixed-base Airbus A320 simulator. A within-subject design was used and eye-tracking data were collected to analyze scanning behavior. RESULTS: The results confirm that the absence of the PM affects the PF's scanning behavior. Participants spent significantly more time scanning secondary instruments at the expense of primary instruments when flying alone. Moreover, the frequency of transitions between the cockpit instruments and the external view increased while mean dwell durations on the external view decreased. CONCLUSION: The findings suggest that the PM supports the PF to achieve efficient scanning behavior. Information should be presented differently in commercial SPO to compensate for the PM's absence and to avoid visual overload. APPLICATION: This research will help inform the design of commercial SPO flight decks providing adequate support for the pilot particularly in terms of efficient scanning behavior.

A low-altitude public air route network for UAV management constructed by global subdivision grids.

With an increasing number of unmanned aerial vehicles (UAVs), the difficulty of UAV management becomes more challenging, especially for low-altitude airspace due to complicated issues of security, privacy and flexibility. Existing management approaches to UAV flights include implementing registration of flight activity for supervision purposes, limiting the maximum flight height, setting different zones for different flight activities and prohibiting flights. In this research, we proposed a new air traffic management method for UAVs based on global subdivision theory. We designed four types of low-altitude air routes from grids, which correspond to grid sizes of 1.85 km, 128 m, 64 m and 32 m. Utilization of the subdivision grids transforms the complex spatial computation problem into a query process in the spatial database, which provides a new approach to UAV management in the fifth-generation (5G) era. We compared the number and data size of stored track records using longitude and latitude and different grid levels, computed time consumption for air route trafficability and simulated UAV flight to verify the feasibility of constructing this type of air traffic highway system. The amount of data storage and time consumption for air route trafficability can be substantially reduced by subdivision. For example, the data size using traditional expressions of latitude and longitude is approximately 1.5 times that of using a 21-level grid, and the time consumption by coordinates is approximately 1.5 times that of subdivision grids at level 21. The results of the simulated experiments indicate that in the 5G environment, gridded airspace can effectively improve the efficiency of UAV trajectory planning and reduce the size of information storage in the airspace environment. Therefore, given the increasing number of UAVs in the future, gridded highways have the potential to provide a foundation for various UAV applications.

The Episode of National Lockdown in the Pandemic: Air Traffic Restriction as the Control Strategy and Its Impact on Existing Cases and Recovery Rate of Novel Coronavirus Disease in Megacities of China.

OBJECTIVE: The effectiveness of air traffic restriction in containing the spread of infectious diseases is full of controversy in prior literature. In January 2020, the Civil Aviation Administration of China (CAAC) announced air traffic restriction in response to the coronavirus disease (COVID-19) pandemic. This study's aim is to empirically examine the policy effectiveness. METHOD: The data from 2 third-party platforms are used in this investigation. The COVID-19 data from the platform DXY and the air traffic data from Airsavvi are matched to each other. The robust panel regression with controlling city effect and time effect is conducted. RESULTS: The curvilinear relations are found between the air traffic restriction and the existing cases, and the recovery rate (quadratic term = 9.006 and -0.967, respectively). As the strength of air traffic restriction is growing, the negative effect (-8.146) of air traffic restriction on the existing cases and the positive effect (0.961) of air traffic restriction on the recovery rate, respectively, begin decreasing. CONCLUSION: On the macro level, the air traffic restriction may help alleviate the growth of existing cases and help raise the recovery rate of COVID-19 in megacities of China, but both these effects will marginally recede as the restriction strength is intensifying.

Incidence and risk factors associated with injuries during static line parachute training in Royal Thai Army.

BACKGROUND: Incidence and risk factors of parachute injuries has been studied in developed countries, but not in trainees of the airborne forces in the Royal Thailand Army. METHODS: A prospective cohort study was conducted among 992 military personnel who attended the basic airborne training program from February to July 2018. Information sheets were used to collect data about (a) personal demographics; (b) environmental conditions surrounding the parachute practice; and (c) parachute-related injuries. The incidence rate of injury was then calculated. Risk factors were examined using multilevel Poisson regression analysis and presented as incidence rate ratio (IRR) and 95% confidence interval (95% CI). RESULTS: A total of 166 parachute-related injuries occurred in 4677 jumps. The incidence rate of injury was 35.50 per 1000 jumps (95%CI: 30.04-41.21). Factors significantly related to parachute injury included: jumping with equipment versus without equipment [adjusted IRR (95% CI): 1.28 (0.88-1.87)], higher wind speed [1.54 (1.27-1.87) per knot], airplane versus helicopter exit [1.75(0.68-4.55)], side versus rear exit [2.13 (1.43-3.23)], night versus day jumping [2.19 (0.81-5.90)], and presence of motion sickness [3.43 (1.93-6.92)]. CONCLUSIONS: To prevent military static line parachute injuries, the following factors should be taken into consideration: type of aircraft, aircraft exit, time of the day, equipment, motion sickness and wind speed. TRIAL REGISTRATION: The project was certified by the Research Ethics Committee, Faculty of Medicine, Chulalongkorn University (IRB No. 697/60).

Beyond safety drivers: Applying air traffic control principles to support the deployment of driverless vehicles.

By adopting and extending lessons from the air traffic control system, we argue that a nationwide remote monitoring system for driverless vehicles could increase safety dramatically, speed these vehicles' deployment, and provide employment. It is becoming clear that fully driverless vehicles will not be able to handle "edge" cases in the near future, suggesting that new methods are needed to monitor remotely driverless vehicles' safe deployment. While the remote operations concept is not new, a super-human driver is needed to handle sudden, critical events. We envision that the remote operators do not directly drive the vehicles, but provide input on high level tasks such as path-planning, object detection and classification. This can be achieved via input from multiple individuals, coordinated around a task at a moment's notice. Assuming a 10% penetration rate of driverless vehicles, we show that one remote driver can replace 14,840 human drivers. A comprehensive nationwide interoperability standard and procedure should be established for the remote monitoring and operation of driverless vehicles. The resulting system has potential to be an order of magnitude safer than today's ground transportation system. We articulate a research and policy roadmap to launch this nationwide system. Additionally, this hybrid human-AI system introduces a new job category, likely a source of employment nationwide.

On the feasibility of the Rayleigh cycle for dynamic soaring trajectories.

Dynamic soaring is a flight technique used by albatrosses and other birds to cover large distances without the expenditure of energy, which is extracted from the available wind conditions, as brightly perceived five centuries ago by Leonardo da Vinci. Closed dynamic soaring trajectories use spatial variations of wind speed to travel, in principle, indefinitely over a prescribed area. The application of the concept of closed dynamic soaring trajectories to aerial vehicles, such as UAVs, may provide a solution to improve the endurance in certain missions. The main limitation of dynamic soaring is its dependence on the wind characteristics. More than one century ago, Lord Rayleigh proposed a very simple model, based on the repeated crossing of a step wind profile, presently known as Rayleigh cycle, that provides a clear explanation of the physical phenomenon. The present paper studies the feasibility of closed, single-loop, energy-neutral trajectories for a broad set of wind and vehicle conditions. Through the use of trajectory optimization methods, it was possible to see how the shape of the wind profile, the initial flight conditions and the vehicle constraints influence the required wind strength to perform dynamic soaring trajectories and consequently their feasibility. It was possible to conclude that there are optimal values for the initial airspeed and initial height of the vehicle, that minimize the required wind strength. In addition, it was seen how the structural and aerodynamic constraints of the vehicle affect dynamic soaring at high and low airspeeds respectively. Finally, some new trajectories that can be performed in conditions of excess wind are proposed. The purpose is to maximize the time spent aloft and the path length while maintaining the concept of single-loop, energy-neutral trajectories, making them especially useful for aerial vehicles surveillance applications.

Comparing the Evolution of Risk Culture in Radiation Oncology, Aviation, and Nuclear Power.

OBJECTIVES: All organizations seek to minimize the risks that their operations pose to public safety. This task is especially significant if they deal with complex or hazardous technologies. Five decades of research in quantitative risk analysis have generated a set of risk management frameworks and practices that extend across a range of such domains. Here, we investigate the risk culture in three commercial enterprises that require exceedingly high standards of execution: radiation oncology, aviation, and nuclear power. METHODS: One of the characteristics of high reliability organizations is their willingness to learn from other such organizations. We investigate the extent to which this is true by compiling a database of the major publications on risk within each of the three fields. We conduct a bibliographic coupling analysis on the combined database to identify connections among publications. This analysis reveals the strength of engagement across disciplinary boundaries and the extent of cross-adoption of best practices. RESULTS: Our results show that radiation oncology is more insulated than the other two fields in its adoption and propagation of state-of-the-art risk management tools and frameworks that have transformed aviation and nuclear power into high reliability enterprises with actuarially low risk. CONCLUSIONS: Aviation and nuclear power have established risk cultures that cross-pollinate. In both nature and extent, we found a distinct difference in radiation oncology's engagement with the risk community, and it lags behind the other two fields in implementing best practices that might mitigate or eliminate risks to patient safety.

A contralateral wing stabilizes a hovering hawkmoth under a lateral gust.

Previous analysis on the lateral stability of hovering insects, which reported a destabilizing roll moment due to a lateral gust, has relied on the results of a single wing without considering a presence of the contralateral wing (wing-wing interaction). Here, we investigated the presence of the contralateral wing on the aerodynamic and flight dynamic characteristics of a hovering hawkmoth under a lateral gust. By employing a dynamically scaled-up mechanical model and a servo-driven towing system installed in a water tank, we found that the presence of the contralateral wing plays a significant role in the lateral static stability. The contralateral wing mitigated an excessive aerodynamic force on the wing at the leeward side, thereby providing a negative roll moment to the body. Digital particle image velocimetry revealed an attenuated vortical system of the leading-edge vortex. An excessive effective angle of attack in the single wing case, which was caused by the root vortex of previous half stroke, was reduced by a downwash of the contralateral wing. The contralateral wing also relocated a neutral point in close proximity to the wing hinge points above the actual center of gravity, providing a practical static margin to a hovering hawkmoth.

An Innovative Technique for Identification of Missing Persons in Natural Disaster Based on Drone-Femtocell Systems.

The recent development of the IoT (Internet of Things), which has enabled new types of sensors that can be easily interconnected to the Internet, will also have a significant impact in the near future on the management of natural disasters (mainly earthquakes and floods) with the aim of improving effectiveness in research, identification, and recovery of missing persons, and therefore increasing the possibility of saving lives. In this paper, more specifically, an innovative technique is proposed for the search and identification of missing persons in natural disaster scenarios by employing a drone-femtocell system and devising an algorithm capable of locating any mobile terminal in a given monitoring area. In particular, through a series of power measurements based on the reference signal received power (RSRP), the algorithm allows for the classification of the terminal inside or outside the monitoring area and subsequently identify the position with an accuracy of about 1 m, even in the presence of obstacles that act in such a way as to make the propagation of the radio signal non-isotropic.

Leading article: What has an Airbus A380 Captain got to do with OMFS? Lessons from aviation to improve patient safety.

The understanding of why air accidents occur and all the factors involved with them has been a strong and constantly evolving driver for improving flight safety. While they are diverse professions, there are many similarities between flying commercial aircraft and surgery, particularly in relation to minimising risk and managing potentially fatal or catastrophic complications. Safety developments in the operating theatre seem to have lagged behind other High Risk Organisations (HROs). A 2018 Quality Care Commission report stated that never events are wholly preventable and expressed the need to learn from other industries. In this article we discuss various transferable lessons and procedures advocated from aviation that could be applied to OMFS in an attempt to improve team culture and safety for our patients.