Browse Topic: Human factors
The development of an adaptive pilot model for rotorcraft tracking tasks is useful to understand and replicate human pilot behavior under varying vehicle dynamics and environmental conditions. This paper presents a Model-Reference Adaptive Control (MRAC)-based pilot model designed to emulate the adaptability of human pilots during attitude and position tracking tasks. The model leverages wavelet analysis to characterize pilot behavior and employs a closed-loop system identification approach to derive baseline pilot parameters. MRAC methodology using state-feedback is implemented and validated through simulations involving time-varying vehicle dynamics, such as changes in control sensitivity and added phase delays. Results demonstrate the model's ability to maintain consistent tracking performance despite dynamic modifications, though discrepancies with human pilot data highlight the complexity of fully capturing adaptive human control strategies. The proposed model offers a framework
As part of a human factors research project aimed at optimizing technical documentation used in helicopter maintenance with multimedia elements, we compared different instruction formats to observe their effects on the performance of an assembly task. This task offers us the opportunity to test procedures that call for similar actions as a maintenance task (e.g., localization, action sequencing, assembly). Static (i.e., image and image with text) and dynamic instruction formats (i.e., video, video with text and video with audio) were compared to determine if dynamic formats allowed a better motor performance of the task for assembly reaction time (time needed to complete the assembly) and accuracy. We were also interested in how the use of the text instructions interacted with both visual dynamic and static instructions. Reaction times were recorded and measured with eye tracking data. Subjective data was collected in questionnaires during and after the experiment. Results showed
This paper examines the Handling Quality Rating (HQR) of the Model-Based Pilot Controller (MBPC) in failure scenarios within the Automatic Flight Control System (AFCS). The MBPC aims to automate the testing of malfunctions in the AFCS of the T625 Gökbey platform. It is constructed using optimal control and estimation theory, with the cost function representing human characteristics determined by weighting matrices. The optimal values of weighting matrices that minimize the cost function are achieved via Genetic Algorithm. This algorithm utilized to systematically minimize user-defined cost functions tailored to optimize performance for selected maneuvers within the scope of ADS33E-PRF, considering user-defined constraints. Time-domain metric performance is provided for two maneuvers: vertical maneuver and hovering turn. The HQRs of the MBPC evaluated according to Power Frequency and Inceptor Peak Power-Phase (IPPP) metrics. The MBPC satisfies the ADS33 desired performance criteria in
Piloted simulation has been used for decades to support flight test activities at the Naval Air Warfare Center Aircraft Division located at Naval Air Station Patuxent River, MD. Conventional lab stations at the Manned Flight Simulator facility have been used effectively to support a wide range of flight test requirements. However, there were limitations with these conventional lab stations when the purpose was to assess handling qualities and pilot workload while landing rotorcraft aboard a ship. Two critical simulation elements were determined to be necessary: (1) an expanded field of view so the pilot could see the ship deck below the aircraft and (2) a motion system to provide the pilot with vital proprioceptive cueing in the turbulent ship environment. A new Virtual Reality Lab was developed at Patuxent River that included these key features. The primary components of the lab included virtual reality headsets, an Unreal Engine image generator, ocean and ship visual models, a six
ABSTRACT Rotorcraft shipboard landing continues to be challenging due to increased pilot workload in dealing with effects of ship air wake turbulence on vehicle motion and random ship motion. Some of the recent work has proposed a pilot assist function for reduced pilot workload using model predictive control methods. This paper explores the use of a recently developed Model Predictive Path Integral (MPPI) method based on a stochastic optimal control framework for trajectory guidance solution to the shipboard landing problem. First, a proof-of-concept study is presented by applying the MPPI method to a simple point mass approximation of helicopter dynamics represented in the form of a first-order command acceleration model, representative of helicopter trajectory motion in the vertical plane. Next, the MPPI method is used in conjunction with a six degrees-of-freedom linear model of a helicopter in order to gain further insight into the applicability of the MPPI framework to the
ABSTRACT Shipboard operations present a unique set of challenges to the pilot-vehicle system. This work addresses problems specific to piloted rotorcraft in the simulated shipboard environment, namely cueing and ship motion, and represents the completion of a three-year effort focused on fixed-base, pilot-in-the-loop rotorcraft flight simulations. Instructors from the United States Naval Test Pilot School, with extensive operational and test experience, participated in the study. Two cueing sets, one for the approach task and another for the hover task, were developed in order to provide intuitive guidance of cyclic and collective inputs. Data were gathered for each task with the cueing system both on and off. The evaluation criteria used to determine the usefulness of the provided cueing were based on pilot workload assessment, profile performance and inceptor activity. The approach task cueing provides the pilot with a preset approach profile defined by altitude and airspeed cueing
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The devices of this SAE Standard provide the means by which passenger compartment dimensions can be obtained using a deflected seat rather than a free seat contour as a reference for defining seating space. All definitions and dimensions used in conjunction with this document are described in SAE J1100. These devices are intended only to apply to the driver side or center occupant seating spaces and are not to be construed as instruments which measure or indicate occupant capabilities or comfort. This document covers only one H-point machine installed on a seat during each test. Certified H-point templates and machines can be purchased from: SAE International 400 Commonwealth Drive Warrendale, PA 15096-0001 Specific procedures are included in Appendix A for seat measurements in short- and long-coupled vehicles and in Appendix B for measurement of the driver seat cushion angle. Specifications and a calibration inspection procedure for the H-point machine are given in Appendix C
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Autorotation is a challenging maneuver during which pilot workload is high. Consequences of an improperly performed maneuver are potentially catastrophic, thus partial automation and/or pilot cueing can potentially be used to reduce pilot workload and increase the probability of a successful landing. This paper describes the development of a nonlinear model predictive control (MPC) scheme and a trajectory generation method that can be used to perform autorotations autonomously, or in development of pilot aids. The proposed control scheme offers potential benefits over existing methods by balancing simultaneous control objectives of trajectory tracking and rotor speed regulation. Results are presented for a six-degree-of-freedom simulation of the AH-1G aircraft. The results are compared to a traditional cascaded PID control scheme to demonstrate the benefits of the MPC algorithm. A trade study is presented in which the target landing point is varied to quantify the benefits of the MPC
Collins Aerospace, through its Common Avionics Architecture System (CAAS) and Flight2 avionics management systems for rotary wing aircrafts, provides extensive video processing, internal graphics generation, and overlay capabilities on real time video streamed from onboard EO/IR cameras providing situational awareness to the pilot in clear day-light and reduced visibility/night conditions. This capability has served our customers well in their cargo, assault, and multi-mission roles, improving the effectiveness of their missions. We now realize that more can be done to reduce pilot workload and enhance mission effectiveness by extracting visual intelligence from the video feed using machine vision. In this paper we explore the use of deep learning based computer vision to extract visual intelligence from onboard video feed and use it to automate low risk pilot actions, such as automatic detection and tracking of objects of interest, panning to maintain focus on objects, zooming on to a
The National Research Council of Canada and Université de Sherbrooke performed flight testing of an Actively Stabilized Slung Load on the NRC Bell 206 Research Aircraft. Hover, Attitude Capture, NRC designed Lateral Precision Hover, and Frequency Sweep mission tasks were performed for bare airframe and slung load aircraft configurations. The load mass ratio was 0.12 while the slung load pendulum mode was 1.3 rad/sec at a damping ratio of 0.2 for the 40-pound per active tether saturation load system setting. Time domain response indicated that the load remained controllable with damped and underdamped behaviors. Frequency domain analyses confirmed pilot comments indicating HQR 4 handling qualities ratings for bare airframe and stable slung load behavior. This rating degraded to HQR 5 for task execution with slung load oscillation. Pilot workload was due to lateral cycle input requirements of 2 to 3 inch amplitudes at 1 to 2 Hz frequency. Operationally, the coincidence of pilot inputs
A core mission of the CH-53K involves flying in severe brownout conditions, which increases pilot workload and can reduce mission success rates. With state of the art Fly by Wire capability, the CH-53K leverages the computational power of a flight control computer to provide higher order control modes which reduce pilot workload in all degraded visual environments such as brownout. The preliminary design of the flight control system included the inceptor system and low speed control architecture, which created an expansive design space. High fidelity simulations, cockpit mockup, and use of the NRC Bell 412 in-flight simulation Advanced Systems Research Aircraft surrogate aircraft allowed for a comprehensive development environment to narrow down to final control system design. The final design of the low speed maneuvering provided a command strategy similar to translational rate commend yet provided an approach profile that more closely replicated a piloted approach to a landing zone
This paper describes the development of full flight envelope dynamic inversion outer-loop control laws used to control airspeed and flight path for two Future Vertical Lift-relevant rotorcraft configurations - a lift offset coaxial helicopter with a pusher propeller and a tiltrotor. The outer-loop control laws for both aircraft include a control allocation scheme to account for redundant controls and reduce pilot workload. A piloted simulation experiment was conducted at the Penn State Flight Simulator facility using a series of high-speed handling qualities demonstration maneuvers to evaluate the handling qualities of the control laws. Overall, the outer-loop control laws for both coaxial-pusher and tiltrotor aircraft were assigned Level 1 handling qualities for the Break Turn and High-Speed Acceleration/Deceleration tasks, and reduced pilot workload over previously developed inner-loop control laws. The outer-loop control laws also improved performance and reduced pilot workload in a
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