An eye-hand movement Model for traffic complexity evaluation and monitoring enhancement for air traffic controllers

• Main Author: Wee, Hong Jie
• Other Authors: Lye Sun Woh
• Format: Thesis-Doctor of Philosophy
• Language: English
• Published: Nanyang Technological University 2020
• Subjects: Engineering::Aeronautical engineering; Engineering::Industrial engineering::Human factors engineering
• Online Access: https://hdl.handle.net/10356/137774
• Institution: Nanyang Technological University

Dynamic changes in the field of Air Traffic Management in recent years, coupled with the increasing use of automation and new concepts like 4-Dimensional Trajectory Based Operations (4D-TBO) are being investigated. It is therefore postulated that future Air Traffic Controller (ATCO) tasks would likely be dedicated to performing more tactical monitoring activities presented on radar displays with lesser communication with the flight crew under regular circumstances, changing the way how ATCOs operate. This brings about a new set of challenges to ATCOs, as current approaches to address issues related to an ATCO’s tactical control activity both operationally and in training, remain limited, due to the lack of knowledge extraction and representation of this activity. This is seen in three different aspects, which are namely the lack of exploitation of shared information between the physical heterogeneous data capture systems with human operated functions; the inadequate representation of tactical air traffic complexity; and the shortage of methods in extracting and representing an ATCO’s monitoring behaviour of the air traffic situation. This research presents a new eye-hand movement model for traffic complexity evaluation and monitoring enhancement for ATCOs under radar surveillance. This eye-hand movement model seeks to integrate information from both dynamic radar and human data streams in real time, while being synchronous. To achieve this goal, efforts were devoted to addressing the three aspects of an ATCO’s tactical monitoring behaviour, comprising the exploitation of shared information between human and system operated functions, the depiction of tactical air traffic complexity and the determination of an ATCO’s perception and comprehension level. An innovative measurement for the tactical monitoring activity of ATCOs, through the establishment of a data activity register frame, which allows for new knowledge extraction and representation in ATC, is first presented. Using a real time eye tracking system, an ATCO’s monitoring behaviour is exploited and analysed by integrating the two sets of activity data (air traffic flight movements and eye tracking metrics) in a highly dynamic changing and synchronous manner in real-time with respect to both spatial and time frames, through the “Dynamic Data Alignment and Timestamp Synchronisation Model”. Test results reveal that this model can synchronise the timestamp of the eye and dynamic display data, align both of these data spatially, while taking into account dynamic changes in space and time on a simulated radar display. This system can also distinguish and show variations in the monitoring behaviour of participants. As such, new knowledge can be extracted and represented through this innovative interface, which can then be applied to other applications in the field of electronic surveillance to unearth monitoring behaviour of the human surveillance operator. A tactical complexity model, herein known as Conflict Activity Level (CAL), is then presented to depict tactical air traffic complexity. This is achieved by evaluating the likely aircraft flight shape profile based on its current and projected position and trajectory. From the flight shape profile, CAL values are computed based on instantaneous existing traffic numbers in the overall region or sub-regions of interest. The proposed complexity approach shows good agreement with other methods in terms of ranking the order of complexity of various air traffic scenarios and the key influencing factors contributing to conflict. In addition, the CAL – Separation Axes Theorem (CAL-SAT) model, capable of calculating the tactical complexity time profile between aircraft pairings based on their instantaneous flight information is also presented. Using this model, the dynamic traffic flow characteristics of the aircraft and the network characteristics of its projected tactical complexity across time can be achieved mathematically. This could assist ATCOs in the adoption of appropriate tactical control strategies. Application of the CAL-SAT model to two realistic ATC situations highlights the different possible tactical control strategies that can be adopted by ATCOs. Better task prioritisation, time management and greater certainty in the deployment of tactical control strategies by ATCOs were observed. Furthermore, watch managers and airspace designers could also benefit, through proper allocation and duration of shift duties assigned to respective ATCOs and the consideration of tactical complexity while designing the airspace respectively. Three eye signatures that combine both eyeball and hand movement of an ATCO are presented. These signatures seek to capture and evaluate the perception and comprehension level of ATCOs for the different tactical monitoring activities. The aligned fixation peak signature, fixation-click count signature and RCG time entropy signature are able to determine the crossing monitoring, aircraft frequency switch and generic flight path monitoring behaviour of ATCOs respectively. Differences in the monitoring behaviour are observed between expertise level and also between the characteristics of these different activities. Test results show that participants with more experience are more likely to exhibit aligned fixation peaks in the crossing monitoring activity as well as more consistent in exhibiting RCGs on the aircraft for the generic flight path monitoring activity. As such, these signatures can therefore be used to distinguish the monitoring behaviour of participants across different expertise level and also for assisting ATCOs in their tactical monitoring tasks under various circumstances. For the aircraft frequency switch activity, test results also show that the action of fixation-click is noticeable for participants for both ‘UCO’ and ‘TOC’ commands. As a result, alerts can be triggered operationally when ATCOs fail to perform at a specified level and the training of prospective ATCOs can thus evaluated more objectively by instructors. This would pave the way for new operational standards and training methods to be developed in future. Lastly, the eye-hand movement model is evaluated by integrating the traffic complexity and corresponding eye signatures synchronously, to deduce the likely strategies that ATCOs deploy in managing their tactical monitoring activities. For activity of aircraft crossing with potential conflict, test results suggest that the expert participant exhibited the aligned fixation peak signature for the purpose of maintaining vertical separation early and to keep awareness of the aircraft pair-in-crossing. For the activity of generic flight path monitoring, test results suggest that the expert participant likely deploys the strategy of monitoring an aircraft more often when a command needs to be issued. This could pave the way for alerts catering to an ATCO’s monitoring strategy to be developed operationally, thereby improving its effectiveness. In training, instructors could also provide curated feedback to the trainees in order to speed up the training process.