Cognitive model of team cooperation in en-route air traffic control

Soraji, Yusuke; Furuta, K.; Kanno, Taro; Aoyama, Hisae; Inoue, Shunsuke; Karikawa, Daisuke; Takahashi, Makoto

doi:10.1007/s10111-010-0168-x

Cited by 18 publications

(4 citation statements)

References 21 publications

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“…Field studies are therefore considered the recommended approach for studying uncertainty (Klein et al 2003;Lipshitz et al 2001) and have been used to study a wide range of cognitive and collaborative processes in ATC operations (c.f. Mackay 1999;Sharples et al 2007;Soraji et al 2012). …”

Section: Methodsmentioning

confidence: 99%

Uncertainty management in enroute air traffic control: a field study exploring controller strategies and requirements for automation

Corver¹,

Grote

2016

Cogn Tech Work

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The management of uncertainty is a critical aspect of current as well as future air traffic control operations. This study investigated: (1) sources of uncertainty in enroute air traffic control, (2) strategies that air traffic controllers adopt to cope with uncertainty, (3) the tradeoffs and contingencies that influences the adoption of these uncertainties, and (4) the requirements for system design that support controllers in following these strategies. The data were collected using a field study in two enroute air traffic control centres, involving ''over the shoulder'' observation sessions, discussions with air traffic controllers, and document analysis. Three types of uncertainty coping strategies were identified: reducing uncertainty, acknowledging uncertainty, and increasing uncertainty. The RAWFS heuristic (Lipshitz and Strauss in Organ Behav Hum Decis Process 69:149-163, 1997) and anticipatory thinking (Klein et al. in Anticipatory thinking, Proceedings of the eighth international NDM conference, Pacific Grove, CA, 2007) were used to identify reduction and acknowledgement strategies. Recent suggestions by Grote (Saf Sci 71:71-79, 2015) were used to further explore strategies that increase uncertainty. The study presents a new framework for the classification of uncertainties in enroute air traffic control and identified the uncertainty management strategies and underlying tactics, in context of contingencies and trade-offs between operational goals. The results showed that controllers, in addition to reducing and acknowledging uncertainty, may deliberately increase uncertainty in order to increase flexibility for other actors in the system to meet their operational goals. The study describes new tactics for acknowledging and increasing uncertainty. The findings were summarized in the air traffic controller complexity and uncertainty management model. Additionally, the results bring to light system design recommendations that allow controllers to follow these different coping strategies, including (1) the design of alerts, (2) the transparency of prediction tools, and (3) system flexibility as a requirement for acknowledging and increasing uncertainty. The results are particularly important as uncertainty is likely to increase in future operations of enroute air traffic control, requiring automation support for controllers. Implications for future air traffic management scenarios as envisioned within the SESAR Joint Undertaking (SESAR JU in European ATM Master Plan, 2 eds, 2012) and NextGen (FAA in FAA's NextGen implementation plan, 2014) operational concepts are discussed.

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Section: Methodsmentioning

confidence: 99%

Uncertainty management in enroute air traffic control: a field study exploring controller strategies and requirements for automation

Corver¹,

Grote

2016

Cogn Tech Work

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“…Another method for extracting cognitive processes is to have the subject speak their thoughts (e.g., Green and Gilhooly 1990;Soraji et al 2012). This involves presenting a subject with a task and having them talk about what they were thinking while completing the task.…”

Section: Outline Of Previous Experimentsmentioning

confidence: 99%

Development of training method for vessel traffic service based on cognitive process

2021

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Vessel traffic service (VTS) is important to protect the safety of maritime traffic. Along with the expansion of monitoring area per VTS operator in Tokyo Bay, Japan, inexperienced operators must acquire the ability to quickly and accurately detect conditions that requires attention (CRAs) from a monitoring screen. In our previous study (Song B, Itoh H, Kawamura Y, Fukuto J (2018) Analysis of Cognitive Processes of Operators of Vessel Traffic Service. In: Proceedings of the 2018 International Association of Institutes of Navigation. IAIN 2018, pp 529–534, Song et al., J Jpn Inst Navig 140:48–54, 2019), we established a task analysis method based on the assumption that the cognitive process model consists of three stages: “situational awareness”, “situation judgment”, and “decision making”. A simulation experiment was conducted for VTS operators with different levels of ability and their cognitive processes were compared based on the observation of eye movements. The results showed that the inexperienced operators’ abilities to predict situation changes were lower. And it was considered that oral transmission of the knowledge is difficult, thus new training methods are needed to help the inexperienced operators to understand the prediction methods of experienced operators. In this study, based on the cognitive process of an experienced operator, we analyzed the prediction procedures of situation changes and developed an educational tool called vessel traffic routine (VTR). The training method learning VTR aims to quickly improve inexperienced VTS operators’ abilities to predict situation changes. A simulation verification experiment of the VTR effect was conducted for four inexperienced operators, who were divided into two groups with and without prior explanation of VTR. By evaluating the cognitive processes of inexperienced operators, it was confirmed that those given prior explanations of VTR were better at detecting CRAs.

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“…However, like human-factor studies on SA, few of these studies have considered both team cognition processes and mental contents. Furuta et al [10] developed a computer simulation using a cognitive model of team cooperation for en-route air-traffic control [11] based on ethnographic field observations that incorporated the concept of mutual belief. However, since the purpose of this simulation was to replicate specific scenarios selected from the field observations, the resulting model is case-specific and cannot be generalized for the detailed analysis of cognitive processes.…”

Section: Journal Of Advanced Simulation In Science and Engineeringmentioning

confidence: 99%

Modelling and simulation of cognitive processes in air-traffic control based on mutual beliefs

Ogawa

Kanno

Furuta

2019

JASSE

Self Cite

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Shared situational awareness among air-traffic controllers (ATCOs) and pilots is essential for airport safety. This paper presents models and simulations of cognitive activities that underlie the communications between ATCOs and pilots. This model facilitates the shared situational awareness analysis and can produce quantitative data to inform the design of communications protocols. A simulation using data from the official 1977-Tenerife-accident report, which reveals the cognitive processes that could explain the communications and behavior detailed in the report, suggests alternate explanations. This proof-of-concept test suggests that the proposed model and simulations can be used for analyzing air-traffic control accidents at airports.

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Cognitive model of team cooperation in en-route air traffic control

Cited by 18 publications

References 21 publications

Uncertainty management in enroute air traffic control: a field study exploring controller strategies and requirements for automation

Uncertainty management in enroute air traffic control: a field study exploring controller strategies and requirements for automation

Development of training method for vessel traffic service based on cognitive process

Modelling and simulation of cognitive processes in air-traffic control based on mutual beliefs

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