The influence of pilot's attention allocation on instrument reading during take-off: The mediating effect of attention span

Shao, Feng; Lu, Tianjiao; Wang, Xiuchao; Liu, Zhenfu; Zhang, Yuting; Liu, Xufeng; Wu, Shengjun

doi:10.1016/j.apergo.2020.103245

Cited by 6 publications

(5 citation statements)

References 26 publications

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“…Second, we used pilot performance (completion time and error rate) and NASA-TLX measurements to comprehensively evaluate the use of the touchscreen. However, the analysis of physiological measurements, such as eye movements, electroencephalogram (EEG), and other physiological data, was not conducted in the study [ 69 , 70 ], and future studies could carry out measurements of physiological data to make the results more comprehensive. Third, our study only examined the application of touchscreen and keypad devices in a simple simulated flight environment.…”

Section: Discussionmentioning

confidence: 99%

Research on the Applicability of Touchscreens in Manned/Unmanned Aerial Vehicle Cooperative Missions

Xue

Zhang

2022

Sensors

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The suitability of touchscreens for human–computer interaction in manned/unmanned aerial vehicle cooperative missions remains uncertain, especially in situations that are time-sensitive with variations in difficulty levels. The purpose of this study is to determine the feasibility of touchscreen applications in manned/unmanned aerial vehicle cooperative missions and the magnitude of the effects of time pressure and task difficulty. In contrast to previous studies, a combination of performance and perceptual load measures was used to divide errors into disposition errors, undetected errors, and miscalculation errors to explore specific error mechanisms, set up typical manned/unmanned aerial vehicle cooperative human–computer interaction tasks, and set up antecedent features for potential factors. Thirty subjects participated in an experiment that required the use of touchscreens or keyboards to perform a human–computer interaction task in a simulated manned/unmanned aerial vehicle cooperative mission. Experiments were set at three task difficulties: low, medium, and high, and were matched to a set time pressure or no time pressure for two seconds for low difficulty, three seconds for medium difficulty, and four seconds for high difficulty. The results showed that the touchscreens improved the participants’ response speed at a time pressure of 2 s or less compared with the use of a general input device; however, the task error rate also increased significantly. The higher the task difficulty was, the worse the performance was and the greater the perceived workload of the participants. The application of touchscreens in dynamic environments subjected the participants to greater physical demands. The performance of participants using a keyboard was no better than that when touchscreens were used during the experiment. Moreover, touchscreens did not significantly improve participant performance. The results support the possibility of using touchscreens in manned/unmanned aerial vehicle cooperative missions.

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Section: Discussionmentioning

confidence: 99%

Research on the Applicability of Touchscreens in Manned/Unmanned Aerial Vehicle Cooperative Missions

Xue

Zhang

2022

Sensors

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“…Visual attention has a complex selectivity mechanism, including a topdown processing mechanism influenced by task requirements and a bottom-up processing mechanism influenced by objective stimuli (Desimone & Duncan, 1995). Considerable research has also confirmed that people's attention is driven by subjective consciousness to reflect operational intention (Huo et al, 2020;Volosin & Horváth, 2020;Wang & Chen, 2020), attracted by regional information in the field of vision and reasonably allocated (Bretherton et al, 2020;Shao et al, 2021). In this process, attentional resources are limited; thus, attention allocation affects the degree of information acquisition.…”

Section: Visual Attention Allocation In Teleoperationmentioning

confidence: 99%

Operator visual attention allocation prediction in a robotic arm teleoperation interface

An,

Zhang,

Jiang

et al. 2023

Hum Ftrs & Erg Mfg Svc

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In digital interactive interfaces with high visual workloads, it is important for operators to allocate their limited attentional resources appropriately to ensure efficient information collection. The salience, effort, expectancy, value (SEEV) model, which combines top‐down and bottom‐up attention mechanisms for predicting attention allocation, has been validated in research areas such as piloting, driving, and surgical operations. However, the validity of the SEEV model in the field of robotic arm teleoperation has not yet been thoroughly studied. The primary purpose of this study was to confirm the feasibility of the SEEV model for operator visual attention allocation prediction in a robotic arm teleoperation scenario. The improved ITTI algorithm, distance‐measuring tool, Delphi method, and lowest ordinal algorithm were adopted to qualify the four factors of the SEEV model, which also contributed to salience and expectancy quantification methods. Accordingly, an attention allocation prediction model in a robotic arm teleoperation scene was constructed. To verify the validity of the prediction model, 20 participants were recruited to control the robotic arm using V‐REP simulation software, and their fixation durations were recorded using an eye tracker as an attention allocation indicator. Participants controlled the robotic arm according to the experimental requirements and operational tasks, such as grasping and placing the target. The results demonstrated that the theoretical data based on the SEEV prediction model are significantly related to the proportion of fixation durations. The experiment verifies the suitability of the SEEV prediction model, and it is anticipated to be utilized in the optimization of interactive interfaces for robotic arm teleoperation.

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“…Villafaina, Fuentes-García, Gusi, Tornero-Aguilera, and Clemente-Suárez [9] carried out a flight simulator-based study to collect psychophysiological responses during take-off, landing, air-air attacks, and air-ground attacks for military pilots with EEG and heartbeat rate measurement devices. Shao et al [27] deployed 16 pilots for a simulator-based take-off task and established the relationships among attention span, instrument reading, and eye movement mode using an eye-tracking system with behavioural responses. Koglbauer and Braunstingl [8] evaluated a training method aiming to improve the situational awareness for ab initio student pilots by inviting the student pilots to complete a flight task in a flight simulator.…”

Section: Theoretical Background and Related Workmentioning

confidence: 99%

A Digital Twin-Based Platform towards Intelligent Automation with Virtual Counterparts of Flight and Air Traffic Control Operations

Yiu

Lee

et al. 2021

Applied Sciences

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Automation technologies have been deployed widely to boost the efficiency of production and operations, to trim the complicated process, and to reduce the human error involved. Nevertheless, aviation remains human-centred and requires collaboration between different parties. Given the lack of a collaborative decision-making training platform for air traffic operations in the industry, this study utilises the concept of cyber-physical systems (CPS) to formulate a system architecture for pilots and air traffic control officers training in collaborative decision making by linking and integrating the virtual counterparts of flights and air traffic control operations. Collaborative decision-making training and the corresponding intelligent automation aids could be realised and supported. A performance analysis via a flight task undertaken with different computational load settings was prepared to evaluate the platform’s latency and integrity. The latency is presented using its 95% confidence interval, and integrity is presented using the percentage of data loss during wireless transmission. The results demonstrated convincing performance and a promising system robustness in both domains.

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The influence of pilot's attention allocation on instrument reading during take-off: The mediating effect of attention span

Cited by 6 publications

References 26 publications

Research on the Applicability of Touchscreens in Manned/Unmanned Aerial Vehicle Cooperative Missions

Research on the Applicability of Touchscreens in Manned/Unmanned Aerial Vehicle Cooperative Missions

Operator visual attention allocation prediction in a robotic arm teleoperation interface

A Digital Twin-Based Platform towards Intelligent Automation with Virtual Counterparts of Flight and Air Traffic Control Operations

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