Previous research indicated a need to improve pilot training with regard to understanding of autopilot logic and behavior, especially in non-routine situations. Therefore, we tested the effect of problem-based exploratory training on pilots’ understanding of autopilot functions. Using a moving-base flight simulator, general aviation pilots (n = 45) were trained to diagnose failures either without foreknowledge and guidance (exploratory group), without foreknowledge but with some guidance (exploratory-guidance group) or with foreknowledge and full guidance (control group). They subsequently performed six test scenarios in which their understanding of the effects of failures was tested by requiring them to deduce the failures and select autopilot modes that were still functioning. Those who received exploratory training with guidance were significantly more likely than the other groups to diagnose failures correctly. The exploratory training group also selected the most appropriate functioning autopilot modes significantly faster than the control group. The results suggest that exploratory training with an appropriate level of guidance is useful for gaining a practical understanding of autopilot logic and behavior. Exploratory training may help to improve transfer of training to operational practice, and prevent automation surprises and accidents.

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In moving-base driving simulators, the sensation of the inertial car motion provided by the motion system is controlled by the motion cueing algorithm (MCA). Due to the difficulty of reproducing the inertial motion in urban simulations, accurate prediction tools for subjective evaluation of the simulator's inertial motion are required. In this article, an open-loop driving experiment in an urban scenario is discussed, in which 60 participants evaluated the motion cueing through an overall rating and a continuous rating method. Three MCAs were tested that represent different levels of motion cueing quality. It is investigated under which conditions the continuous rating method provides reliable data in urban scenarios through the estimation of Cronbach's alpha and McDonald's omega. Results show that the better the motion cueing is rated, the lower the reliability of that rating data is, and the less the continuous rating and overall rating correlate. This suggests that subjective ratings for motion quality are dominated by (moments of) incongruent motion, while congruent motion is less important. Furthermore, through a forward regression approach, it is shown that participants' rating behavior can be described by a first-order low-pass filtered response to the lateral specific force mismatch (66.0%), as well as a similar response to the longitudinal specific force mismatch (34.0%). By this better understanding of the acquired ratings in urban driving simulations, including their reliability and predictability, incongruences can be more accurately targeted and reduced.

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Understanding human perception of haptic feedback is critical when designing and regulating these interfaces. In recent years, experiments have been conducted to determine the just-noticeable difference (JND) in mass-spring-damper dynamics, using a hydraulic admittance display in the form of a side-stick. These experiments have resulted in a model of JNDs when interacting with linear second-order dynamics. In real-world applications, however, control force dynamics also commonly include nonlinearities, such as friction. This research extends the current understanding of JNDs in linear systems by including the nonlinear case, where friction is also present. Experiments were conducted to determine JNDs in friction when combined with second-order system dynamics. Results indicate that friction JND can be independent of linear system dynamics as long as its value compared to the linear system's impedance is sufficiently large. As a consequence, friction JND follows Weber's law, also when it is combined with mass-spring-damper dynamics, unless the level of friction approaches the detection threshold, which in turn can be influenced by the linear system dynamics. Based on the findings presented, it is possible to conduct targeted experiments to confirm and add to these initial results.

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Automation errors may result in human performance issues that are often difficult to grasp. Skraaning and Jamieson (2023) proposed a taxonomy for classifying automation errors into categories based on the visible symptoms of design problems, so as to benefit the design of training scenarios. In this paper, we propose a complementary classification that is based on the mechanisms of human-automation interaction guided by Rasmussen’s Skill, Rule and Knowledge (SRK) taxonomy. We identified four main failure classes and expect that this classification can support automation designers.@en

This article discusses a long short-term memory (LSTM) recurrent neural network that uses raw time-domain data obtained in compensatory tracking tasks as input features for classifying (the adaptation of) human manual control with single- and double-integrator controlled element dynamics. Data from two different experiments were used to train and validate the LSTM classifier, including investigating effects of several key data preprocessing settings. The model correctly classifies human control behavior (cross-experiment validation accuracy 96%) using short 1.6-s data windows. To achieve this accuracy, it is found crucial to scale/standardize the input feature data and use a combination of input signals that includes the tracking error and human control output. A possible online application of the classifier was tested on data from a third experiment with time-varying and slightly different controlled element dynamics. The results show that the LSTM classification is still successful, which makes it a promising online technique to rapidly detect adaptations in human control behavior.

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Flying wings are known for their limited lateral-directional stability and handling qualities. This study aims at assessing the lateral-directional handling qualities of a conceptual flying wing aircraft currently in development at TU Delft, the Flying-V, in a moving-base flight simulator. It focuses on two aspects: First assess the lateral-directional handling qualities of the bare-airframe Flying-V, and the compliance to quantitative requirements. Second, improve these handling qualities through a prototype flight control system, and assess its effect on the handling qualities and the requirement compliance. These assessments were performed both analytically and with a pilot-in-the-loop simulator experiment, in order to experimentally validate analytical findings and obtain new pilot-subjective insights. The analytical and experimental assessment for lowspeed flight conditions both show the lateral-directional handling qualities of the Flying-V to be insufficient for requirement compliance, due to a lack of pitch, roll and yaw control authority and an insufficiently stable Dutch roll eigenmode. The prototype flight control system, consisting of an adapted control allocation and a stability augmentation system, showed both analytically and experimentally to improve the control authority, stability, and handling qualities of the Flying-V. While the effect on the lateral-directional stability was sufficient for stability requirement compliance, the control authority was not sufficiently increased for maneuverability requirement compliance at low speed. Thus, if the landing speed is not increased from the current baseline, a challenge remains to improve the handling qualities of the Flying-V. An approximation of the control authority required for full requirement compliance in the low-speed flight conditions tested showed a control authority increase of over a factor four to be required in that case.@en

Accurate process control through automation is the key to achieving efficient and stable operation of a blast furnace. In this study, we developed an automatic control system of hot metal temperature (HMT). To cope with the slow and complex process dynamics of the blast furnace, we constructed a control algorithm that predicts eight-hour-ahead HMT using a two-dimensional (2D) transient model and calculates optimal target pulverized coal ratio (PCR) and pulverized coal flow rate by non-linear model predictive control (NMPC). An evaluation in a real plant showed that the developed control system suppressed the effects of disturbances, such as changes in the coke ratio and blast volume, on the HMT. The root mean square (RMS) of the control deviation of HMT was successfully reduced by 1.6 °C compared to the conventional manual operation.

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In the design of human-like steering support systems, driver models are essential for matching the supporting automation's behavior to that of the human driver. However, current driver models are very limited in capturing the driver's adaptation to key task variables such as road width and visibility (i.e., 'preview' of the road ahead). This paper uses a recently proposed, novel control-theoretical model for centerline tracking to investigate driver steering in lane-keeping tasks with restricted and unrestricted preview, in an attempt to substantially extend this model's validity. Using data from a tailored driving simulator experiment, three driver control loops (feedforward, heading and position feedback) are separately quantified using system identification techniques. The results show that when preview is restricted, drivers use all of the remaining preview to anticipate the curves of the road ahead, and are no longer able to 'smooth' tight curves in the road trajectory (i.e., corner cutting). When sufficient preview and lane width are available, the time to line crossing increases, and steering behavior is less aggressive and more intermittent, or more 'satisficing'. The novel driver steering model captures these adaptations very well (over 95% of the steering actions) and can thereby be instrumental in realizing human-like steering automation and support systems.

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Haptic cues on the side stick are a promising method to reduce loss of control in-flight incidents. They can be intuitively interpreted and provide immediate support, leading to a shared control system. However, haptic interfaces are limited in providing information, and the reason for cues may not always be clear to pilots. This study presents the results of the conceptual development of visual display symbology that supports haptic feedback on the side stick in communicating flight envelope boundaries to pilots. Novel indications for the limits of airspeed, load factor, angle of attack, and angle of bank, which for the first time simultaneously indicate magnitude and direction of the haptic cues, were integrated in an Airbus primary flight display. The symbology was tested in a pilot-in-the-loop experiment with professional Airbus pilots (N=16) flying several approaches in alternate law with haptic feedback. Objective results do not show clear improvements, although the time spent outside the flight envelope is slightly reduced. Subjective results indicate a preference, however, for the new display and an increased understanding of the haptic feedback. Further research is recommended to improve the interface design, remove unused indications, and test a bank scenario using current operational bank limits.@en

To alleviate the workload of air traffic controllers, part of the air traffic may be handled by a future automated system. When deciding which flights to delegate, a distinction can be made between basic and non-basic flights, with the former being prime candidates for delegation. The human controller can then focus on the non-basic flights, where human competencies are most valuable and more difficult to automate. The classification of flights is preferably based on objective measures relating to the traffic situation. Existing complexity models are, however, often used for capacity predictions or airspace restructuring and primarily to assess the complexity of a sector as a whole. In this paper we use empirically collected flight complexity ratings from 15 professional en-route air traffic controllers. They indicated which other flights contributed to their complexity assessment of a single flight of interest. This exploratory study was able to build a machine-learning model which adequately classifies these flights, based on a qualified majority of controllers. By analyzing the interactions between the included flights, we discuss whether a classification model can differentiate between basic and non-basic flights, and which traffic features play the largest role. Once this can be done reliably and an appropriate complexity threshold has been chosen, a model can be developed as a starting point for an automatic allocation algorithm that distributes flights between a human controller and the computer.@en

The Continuous Descent Approach (CDA) offers reduced aircraft noise emissions and fuel consumption, but the obstacle limiting it to reduced traffic density conditions, is the low predictability of the trajectory and Estimated Time of Arrival (ETA). The solution proposed by this research is to develop a pilot support interface to facilitate the execution of a fixed flight path angle CDA, where thrust is not limited to idle and a velocity profile can be tracked, which will lead to a selected ETA. Initially, the CDA trajectory was investigated through an aerodynamic model, while the solution space of the ETA and the calculation of the stepwise velocity profile were defined. Following the analysis of the pilot’s role, a two-fold support interface was designed based on Ecological Interface Design (EID), with a Vertical Situation Display (VSD) playing a central role for planning and execution. The interface was tested in a MATLAB®/Simulink® setup and five pilots were recruited to execute simulations over different wind conditions. Their on-time performance was satisfactory, while they worked with the provided cues and suggested some interface changes to offer more flexibility. A more robust application of the proposed approach can lead to a wider adoption of the CDA, as a validated procedure.@en

Due to the non-deterministic nature of longitudinal human driver behaviour, motion cueing algorithms currently cannot fully utilize the workspace of driving simulators. This paper explores the possibility of using various predictor variables to predict longitudinal driving behaviour. Through the development of a logistic regression model, it is shown that a combination of the current vehicle velocity, the speed limit eight seconds ahead and the accelerator pedal deflection yields the most accurate estimate of the probabilities that drivers will accelerate or decelerate. Based on these probabilities, a driving simulator was linearly pre-positioned in combination with a classical washout algorithm. The perceived motion incongruence was subjectively evaluated by the drivers (N = 34), testing: (i) no pre-positioning, (ii) pre-positioning, and (iii) pre-positioning with an increased longitudinal classical washout gain enabled by the pre-positioning. Results show that the pre-positioning improves the margins with respect to the longitudinal workspace limits (better workspace management), without affecting the motion incongruence ratings. When using the increased margins to increase the longitudinal gain, however, no significant reduction in motion incongruence ratings was observed. This is likely due to the small motion space of the hexapod motion system used in the current study. However, this paper shows that longitudinal driving behaviour can be accurately predicted and can enable improved workspace utilization for driving simulators. @en

In driving simulation, the choice of a simulator, motion cueing algorithm, and associated set of tuning parameters for an experiment is typically made with an exclusive focus on the quality of the motion. In practice, many other metrics could affect this choice as well, such as tuning complexity, algorithm stability, or the financial costs of the simulation. Arguably, the complete motion cueing algorithm quality is thus more than the quality of the motion alone. This paper presents results of a survey which attempted to identify the most important metrics from the perspective of the main experiment stakeholders. Four stakeholder groups in typical driving simulator experi- ments are defined: The experimenters, motion cueing engineers, operators, and participants. All groups received the same survey, asking them to indicate how important various metrics are for them. Results show that, next to the quality of the motion, experimenters and participants are generally interested in reducing simulator sickness. The motion cueing engineers rank tuning effort and tuning complexity as most important metrics. Operators prefer an easy to use and overall stable motion cueing. A typical BMW experiment is discussed as example, which shows that the choice for a simulator and motion cueing algorithm can indeed differ when including these metrics in a trade-off, compared to when only motion quality is considered. The presented methods allow for a better, multi- faceted selection of the simulator, motion cueing algorithm, and associated tuning parameters, improving future driving simulation experiments. @en

The Flying-V novel aircraft design aims at reducing fuel consumption by an innovative low-drag, fuselage-free geometry. Possible issues related to certification requirements have been noted, however, regarding longitudinal handling qualities at low speed, the pull-up manoeuver, and the flight-path-angle response. This study aims at investigating these issues through a pilot-in-theloop experiment. Starting with a mathematical model of the Flying-V, based on the vortex lattice method, a preliminary off-line analysis of the handling qualities is conducted. A sensitivity analysis is considered over the proposed operational center-of-gravity range, approach speed (between 0.225 and 0.3 Mach, 149 and 198 knots indicated airspeed, respectively), maximum deflection of the control surfaces (between 20 and 30 degrees), and flight control system (Direct Law or Pitch-Rate Command). The pilot-in-the-loop experiment, its design guided by results from the analytical assessment, shows that the handling qualities provided by the current design of the Flying-V with Direct Law at 0.3 Mach are satisfactory with minor improvements related to aircraft responsiveness. For lower speeds (0.225 Mach), the handling qualities degrade due to a sluggish response, high compensation workload, insufficient control authority, insufficient sight angle, and tendency to pilot induced oscillations. Shifting the center of gravity away from the nose provides larger control authority at the expense of a minor reduction of responsiveness. Control augmentation proves to be very effective at improving the handling qualities. It is expected that the go-around certification standards will be satisfied, but approach speed will remain critical for controllability and safety.

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This paper analyzes the effects of the helicopter dynamics on pilots' learning process and transfer of learned skills during autorotation training. A quasi-transfer-of-training experiment was performed with 10 experienced helicopter pilots in the SIMONA moving-base flight simulator at Delft University of Technology. Pilots had to control an in-house flight dynamics model setup to simulate two types of helicopter dynamics: (1) a "hard"dynamics characterized by a low autorotative flare index requiring high pilot control compensation and (2) a "easy"dynamics characterized by a high autorotative flare index with low pilot control compensation required. Two groups of pilots tested these types of dynamics in a different training sequence: hard-easy-hard (HEH group) and easy-hard-easy (EHE group). The main conclusion of this study proved that simulator training for autorotation can best start with pilots training in the most resource demanding condition. A more challenging helicopter's dynamics will require higher pilot agility and more rapid responses to his/her perceptual changes. This will result in pilots developing more robust and adaptable flying skills. Indeed, a clear positive transfer of training effect was observed in the experiment presented in this paper in terms of acquired pilot skills in the HEH group, but not the EHE group. Positive transfer was especially observed in terms of reduced rate of descent at touchdown. The two groups differed in the control strategy applied, with the HEH group having developed a control technique mimicking more closely the one adopted in a real helicopter.

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In academic air traffic control research, traffic scenarios are often repeated to increase the sample size and enable paired-sample comparisons, e.g., between different display variants. This comes with the risk that participants recognize scenarios and consequently recall the desired response. In this paper we provide an overview of mitigation techniques found in literature and conclude that rotating scenario geometries is most frequently used. The potential impact of these transformations on participant behavior, as described in this paper, is however not sufficiently addressed in most studies. As an example we, therefore, analyze previously collected eye tracking data from ten professional air traffic controllers, each presented with three repetitions in various rotations of several distinct scenarios. Results imply that researchers wishing to repeat scenarios should more carefully consider whether mitigation techniques might have an impact on their results.@en

Expert participants may not always be available for evaluation of new displays or support systems, and in some cases, it might be better to use novice participants, particularly when the display or support significantly changes existing work practices. To provide tools and arguments for selecting the expertise level of participants, we propose the use of Rasmussen’s decision ladder to analyze where and how a new visualization or a support tool changes the task, and identify steps where a novice participant may learn to perform the task to an acceptable level. A comparison to the support with the current operational interfaces then shows where an expert might have difficulty in stepping away from learned practice. This analysis is applied to the domain of air traffic control, and a selected set of relevant past research with both expert and novice participants is reviewed, revisiting the decision for a participant level in the study. @en

A novel aircraft configuration, the tailless Flying-V, is examined for its longitudinal handling qualities in cruise by means of piloted simulations. The Flying-V is controlled by two aileron/elevator (elevon) surfaces on each side, and rudders on each wingtip. Two control allocation schemes were created: a conventional one where both inboard and outboard elevons deflect in the same direction, and one where the change in lift the elevons generate is countered by deploying the inboard and outboard elevons in opposite directions, allowing more direct control of the resulting flight path. The longitudinal handling qualities in cruise conditions were investigated by pilot opinion in a moving base simulator. Three experiments were conducted: a traditional pitch tracking experiment with the conventional control allocation, and a new flight-path-angle tracking experiment, using both the conventional and the flight-path-oriented control allocation. The pilots indicated the conventional pitch attitude control to have Level 1 handling qualities for the pitch control task, and Level 2 for the flight path control task. The flight-path-oriented control allocation improved the performance of the pilots during the flight-part tracking experiment, but the perceived control authority was considered too small for most pilots to consistently rate it at Level 1.@en

Preventing Loss of Control In-flight (LOC-I) in commercial and general aviation is an active research area with numerous proposed solutions. One of these solutions aims to prevent lateral LOC-I, a special type of LOC-I, by presenting a roll-performance based minimum lateral control speed to the pilot in roll-limited situations, such as single-engine failure scenarios in multi-engine aircraft. This minimum lateral control speed is predicted by a system, named the Vc Prediction System (VPS), which continually predicts the minimum lateral control speed Vc at which an aircraft can still obtain a certain roll angle within a certain amount of time. It consists of three components; a linear model, a parameter estimation method and a Vc prediction model. These VPS components were designed for a simulation model of the Piper Seneca. This study analyzes the sensitivity of the VPS design to a change in aircraft dynamics and simulation model complexity by redesigning this system for a high-fidelity simulation model of the Fokker 50. The results show that both aircraft favor a small linear model and the Modified Kalman Method for parameter estimation. The original Vc prediction model however gives higher Vc prediction errors for the Fokker 50 than for the Piper Seneca. By simplifying the original Vc prediction model a stable, smooth and relatively accurate Vc prediction for the Fokker 50 can be obtained.@en

Background. Previous studies and accident analyses have shown that pilots can make roll reversal errors when responding to bank angles shown by the artificial horizon in the Primary Flight Display (PFD). In the current study, we tested whether adding stereoscopic depth cues to the artificial horizon may lead to better bank angle representation due to an improved figureground separation between the symbols. Method. Stereoscopic depth cues were created by using a half-silvered mirror multi-layer PFD, which presented the horizon symbol on a lower layer and the aircraft symbol on a higher layer. A group of 23 non-pilots and 18 general aviation pilots were shown left or right bank angles on this multi-layer PFD as well as on a normal single-layer PFD, with the task to roll the wings level using a joystick. Results. In the pilot group, a similar amount of roll-reversal errors was made with both displays (median = 3.3%) with no significant difference, p = 0.635. In the non-pilot group, fewer roll-reversal errors were observed with the multi-layer display, but this difference did not reach significance either (median = 3.3% vs. 5.0%, p = 0.182). In both pilots and non-pilots, the reaction time was longer in the multi-layer display, which reached significance in the non-pilots (p = 0.016) but not in pilots (p = 0.215). Participants noticed that the depth was only visible during the start of the session. Conclusions. The results suggest that using stereoscopic depth cues are not a viable manner to enhance the figure-ground relation in the artificial horizon. @en