Browse Topic: Reaction and response times
The vertical flight industry is on its way to a transformative era, with autonomous technologies set to alter aerial vehicle operations. While it seems certain that fully autonomous helicopters will eventually be deployed for a variety of missions, some high-stakes situations—like medical evacuations (MEDEVAC)—will for the foreseeable future demand human participation in the form of Emergency Medical Care-giving Crew. This study describes the testbed built to run and investigate hypothetical future situations in which a helicopter is autonomously piloted while a human medic with no aviation training, subjected to aviation and medical emergencies, manages patient care onboard. A total of 22 participants, with emergency medical technician certification, nursing or a medical board certification, were invited to run and evaluate the use of AI pilot (AP) in different scenarios of medical evacuation under the following emergencies: medical, empty fuel tank, pressure sensor miscalibration, and engine failure. A comprehensive evaluation of both objective and subjective performance metrics revealed that novice medical professionals could effectively execute medical evacuation operations in conjunction with an AI pilot, even during unforeseen circumstances. The analysis of response times unveiled distinct perspectives on how medics perceive and manage various emergency situations when an AP functions as a collaborative and effective team member.
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 significant differences in the time spent on the instructions and the time spent on the assembly, depending on the format of instructions. Overall, assembly time is shorter with video instruction formats, but videos took longer to be consulted than static formats. Results also showed a difference in the number of actions required to do the assembly. Videos facilitated the right path of action sequence in comparison with static formats. With the analysis of both subjective and objective data, the results give us a better idea of the advantages and drawbacks of using dynamic formats in technical documentation.
This SAE Information Report provides definitions and discussions of key terms concerning driver drowsiness and fatigue, and basic information on measuring drowsiness and fatigue. It also includes information and concepts for driver drowsiness as they relate to the safe operation of a vehicle. The key driver drowsiness and fatigue causal factors include the following: (1) sleep quality and quantity, (2) time of day, (3) time awake, (4) time on task (modulated by characteristics of the driving task), (5) task-related fatigue (variations of arousal levels related to task underload and overload), and (6) combinations of these factors. Medical conditions, medication, alcohol, or drugs exacerbate drowsiness; however, the discussion in this report is limited to fatigue concepts. This report has two primary outputs: (1) definitions and discussions of key terms concerning driver drowsiness and fatigue, and (2) basic information on measuring drowsiness and fatigue and its effects on the safe operation of a vehicle. These include the physiological and cognitive effects of driver drowsiness and fatigue on driving safety. Examples of effect of driver drowsiness and fatigue on driving safety include those related to vehicle control, operator vigilance (sustained attention), reaction times (object and event detection and response), situational awareness, physiological indicators, subjective assessments, and combinations thereof. For definitions of driving performance measures, refer to SAE J2944. This report applies to all worldwide motor vehicle passenger cars and light trucks, as well as heavy trucks, buses, motorcycles, and mopeds. The intended users of the document are practitioners and researchers in the automotive industry, academia, and other organizations with interest in driver drowsiness and fatigue, driving and driver performance assessment, and road safety.
Future vertical lift (FVL) missions will be characterized by increased agility, degraded visual environments (DVE) and optionally piloted vehicles (OPVs). Increased agility will induce more frequent variations of linear and angular accelerations, while DVE will reduce the structure and quality of the out-the-window (OTW) scene (i.e. optical flow). As helicopters become faster and more agile, pilots are expected to navigate at low altitudes while traveling at high speeds. In nap of the earth (NOE) flights, the perception of self-position and orientation provided by visual, vestibular, and proprioceptive cues can vary from moment to moment due to visibility conditions and body alignment as a response to gravitoinertial forces and internally/externally induced perturbations. As a result, erroneous perceptions of the self and the environment can arise, leading ultimately to spatial disorientation (SD). In OPV conditions, the use of different autopilot modes implies a modification of pilot role from active pilot to systems supervisor. This shift in paradigm, where pilotage is not the primary task, and where feedback from the controls is no more available, is not without consequences. Of importance is the evidence that space perception and its geometric properties can be strongly modulated by the active or passive nature of the displacement in space. An experiment was conducted using the vertical motion simulator (VMS) at the NASA Ames Research Center that examined the contributions of gravitoinertial cueing and visual cueing in a task where the pilot was not in control of the aircraft but was asked to perform altitude monitoring in a simulated UH-60 Black Hawk helicopter with a simulated autopilot (AP) mode. Within the altitude monitoring task, the global optical density (OD), flow rate and visual level of detail (LOD) were manipulated by the introduction of an 18ft vertical drift, upward or downward that simulates a vertical wind shift. Seven pilots were tested in two visual meteorological conditions, good visual environment (GVE) and degraded visual environment (DVE) and two gravitoinertial conditions, where platform motion was either ON or OFF. The results showed that both the good quality of the visual environment and the presence of gravitoinertial cues improved altitude awareness and reduced detection/ reaction times. The improvement of the tracking performance in the visuo-vestibular setting as compared to a visual only setting when the visual cues were poor indicated some level of multisensory integration. Task-dependent limitations of a popular aeronautics metric called DIMSS-PM (Dynamic Interface Modeling and Simulation System Product Metric) and its sub-components were shown, and recommendations for OPV operations were formulated.
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