China
Africa
Explore chapters and articles related to this topic
Task Analysis Methods
Published in Neville A. Stanton, Paul M. Salmon, Guy H. Walker, Chris Baber, Daniel P. Jenkins, Human Factors Methods, 2018
Neville A. Stanton, Paul M. Salmon, Guy H. Walker, Chris Baber, Daniel P. Jenkins
A TTA was performed on the landing task, 'Land aircraft X at New Orleans using the autoland system' (Marshall et al, 2003). The purpose of the analysis was to ascertain how suitable the TTA method was for the prediction of design induced error on civil flight decks. A HTA of the flight task was constructed (Figure 3.6) and a TTA analysis was performed (Table 3.10). Data collection included the following: Walkthrough of the flight task.Questionnaire administered to aircraft X pilots.Consultation with training manuals.Performing the flight task in aircraft simulator.Interview with aircraft X pilot.
Task Analysis Methods
Published in Neville A. Stanton, Paul M. Salmon, Laura A. Rafferty, Guy H. Walker, Chris Baber, Daniel P. Jenkins, Human Factors Methods, 2017
Neville A. Stanton, Paul M. Salmon, Laura A. Rafferty, Guy H. Walker, Chris Baber, Daniel P. Jenkins
Once the overall task goal has been specified, the next step is to break this overall goal down into meaningful sub-goals (usually four or five, but this is not rigid), which together form the tasks required to achieve the overall goal. In the task ‘Land aircraft X at New Orleans Airport using the autoland system’ (Marshall et al., 2003), the overall goal of landing the aircraft was broken down into the following subgoals: ‘Set up for approach’, ‘Line up aircraft for runway’ and ‘Prepare aircraft for landing’. In an HTA of a Ford in-car radio (Stanton and Young, 1999a) the overall task goal, ‘Listen to in-car entertainment’, was broken down into the following sub-goals: ‘Check unit status’, ‘Press on/off button’, ‘Listen to the radio’, ‘Listen to cassette’ and ‘Adjust audio preferences’.
Technological Constraints
Published in Steven D. Jaffe, Airspace Closure and Civil Aviation, 2016
The second phase of the project came six months later as GE and LAN completed an RNP Authorization Required (AR) to instrument landing system (ILS) with autoland at Lima's Jorge Chavez International Airport. The flight combined the predictability and operational benefit of RNP with the lower landing minima and autoland capabilities enabled by the ILS. The combined benefit results in reduced landing minima of 100 ft at Lima, a remarkable development for an airport often shrouded in dense coastal fog. Additionally, the higher navigational precision enabled by RNP opens up airspace to the east of the airport—previously off-limits due to terrain challenges—to be used on the approach. The effect is to free up a section of close-in airspace previously off-limits, providing additional capacity without major ground-based infrastructure investments (CANSO, 2012, Third Quarter).
A supportive situation awareness model for human-autonomy teaming in collaborative driving
Published in Theoretical Issues in Ergonomics Science, 2020
Rinta Kridalukmana, Hai Yan Lu, Mohsen Naderpour
In the HAT context, the mutual SA model can exist in the aviation field. An aircraft feature called Emergency Autoland System (EAS) can be considered as a non-human agent. When both the pilot and co-pilot are disabled, a passenger can activate the EAS, and the EAS will contact the nearest airport listed in its database. After obtaining a response, at this point, the mutual SA model is established between EAS and the air traffic controller officer with the same goal, which is to land the aircraft safely. In this regard, the officer’s task is to manage the air traffic for the landing process performed by EAS. Then, the teaming between an automated unmanned aerial vehicle (UAV) and an army troop can be an example of a shared SA model, in which both have the intersection goal to collect information from a battlefield. Nevertheless, the troop also has a different goal to obtain, i.e. custody, while the UAV must serve another troop. In the meantime, an example of a team SA model is demonstrated by an autonomous robot squad that is assigned to send supplies for a troop. In this regard, both the troop and the robot squad have different goals.
Multisensory Cues for Encoding Urgency of System Hazards: Effect of Operator Experience on Perceived Urgency
Published in The International Journal of Aerospace Psychology, 2019
G. Robert Arrabito, Geoffrey Ho, Yeti Li, Wayne Chi Wei Giang, Catherine M. Burns, Ming Hou
The experiment was carried out on a testbed for the simulation of monitoring the behavior of a UAS, which is a two-screen interface (Arrabito et al., 2013). The left monitor (Figure 1, top panel) displayed the real-time video image of the UAS in flight shown from a camera located on the tail of the aircraft pointing forward. The right monitor (Figure 1, bottom panel) displayed a tactical map of the UAS’s area of operation and instrument panels. The UAS status window provided altitude, heading, air speed, and engine RPM. The warning panel displayed warnings and messages in green, yellow or red, corresponding to a low, medium or high level of urgency (US Department of Defense, 2012). The autoland panel, which appears only when the participant attempts to land the UAS, provided information on landing parameters.