The purpose of this study is to analyse the impact of the cockpit interface design on pilots' attention distribution during flight operations. Two different fighter jet simulators, Fighter-A and Fighter-B, with different interface designs were used in this research. Both Fighter-A and Fighter-B simulators are dynamic, high-fidelity trainers that replicate actual aircraft performance, navigation and weapon systems. Sixty-nine qualified mission-ready pilots 39 Fighter-A pilots, 30 Fighter-B pilots participated in this research. Fighter-A pilots had: ages between 26 and 45 years old Mi¾?=i¾?34, SDi¾?=i¾?5; total flying hours between 372 and 3,200i¾?h Mi¾?=i¾?1294, SDi¾?=i¾?753; and type flying hours between 89 and 2,270i¾?h Mi¾?=i¾?815, SDi¾?=i¾?524. Fighter-B pilots had: ages between 26 and 51 years old Mi¾?=i¾?30, SDi¾?=i¾?6; total flying hours between 310 and 2,920i¾?h Mi¾?=i¾?845, SDi¾?=i¾?720; and type flying hours between 63 and 2,000i¾?h Mi¾?=i¾?461, SDi¾?=i¾?487. Eye movement data were collected by a head-mounted ASL Applied Science Laboratory Mobile Eye, which is 76i¾?g in weight. Eye movements at five areas of interest AOIs were analyzed, since those AOIs provide pilots with the required flight information to accomplish the mission. The AOIs are: Head-up Display HUD; Integrated Control Panel ICP; Right Multiple Function Display RMFD; Left Multiple Function Display LMFD; and Outside of Cockpit OC. The findings indicate that differences in interface design might impact pilots' visual scanning patterns, which is associated closely with attention distribution. This research demonstrated that interface designs of HUD, ICP, RMFD and LMFD of Fighter-A attract a higher percentage of fixation and longer average fixation duration compared with Fighter-B. Furthermore, Fighter-A pilots' perceived workloads were lower, but their situational awareness performance was better than Fighter-B pilots. The application of an eye-tracking device during flight operations is not only beneficial to understand the pilot's attention distribution, but also to understand the interaction performance between the pilot and the interface. The findings of this research have potential benefits for improving interface design and the efficiency of aviation training.
[1]
Feng-Yang Kuo,et al.
An exploratory study of cognitive effort involved in decision under Framing - an application of the eye-tracking technology
,
2009,
Decis. Support Syst..
[2]
Mica R. Endsley,et al.
Toward a Theory of Situation Awareness in Dynamic Systems
,
1995,
Hum. Factors.
[3]
Stephanie M. Doane,et al.
Memory Processes of Flight Situation Awareness: Interactive Roles of Working Memory Capacity, Long-Term Working Memory, and Expertise
,
2004,
Hum. Factors.
[4]
J. Henderson.
Human gaze control during real-world scene perception
,
2003,
Trends in Cognitive Sciences.
[5]
Gary Klein,et al.
Naturalistic Decision Making
,
2008,
Hum. Factors.
[6]
M R Endsley,et al.
Sources of situation awareness errors in aviation.
,
1996,
Aviation, space, and environmental medicine.
[7]
Hasan Ayaz,et al.
Cognitive Workload Assessment of Air Traffic Controllers Using Optical Brain Imaging Sensors
,
2010
.
[8]
Ulf Ahlstrom,et al.
Using eye movement activity as a correlate of cognitive workload
,
2006
.
[9]
John R. Anderson,et al.
Tracing Eye Movement Protocols with Cognitive Process Models
,
1998
.
[10]
Barry Strauch,et al.
Investigating Human Error: Incidents, Accidents, and Complex Systems
,
2002
.
[11]
R. Proctor,et al.
Attention: Theory and Practice
,
2003
.
[12]
Geoffrey R. Loftus,et al.
Eye fixations and memory for emotional events.
,
1991
.
[13]
M. Endsley.
The role of situation awareness in naturalistic decision making
,
1997
.