A closed-loop, ACT-R approach to modeling approach and landing with and without synthetic vision system (SVS) technology

Byrne, Michael D.; Kirlik, Alex; Fleetwood, Michael D.; Huss, David G.; Kosorukoff, Alex; Lin, Ruei-Sung; Fick, Chris S.

doi:10.1037/e577072012-007

Cited by 4 publications

(4 citation statements)

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“…Consequences of an overheard or ignored message for pilots' performance can be anticipated with the help of a cognitive pilot model. ACT‐R (Anderson et al, 2004) is a comprehensive and scientifically substantiated cognitive architecture that has produced models representing processes, for example, involved in “manual” flight control of single engine aircraft (Somers & West, 2013), visual attention allocation in a glass cockpit (Byrne et al, 2004), and the use of and skill acquisition for the flight management system (Schoppek & Boehm‐Davis, 2004; Taatgen, Huss, & Anderson, 2008). For model‐based assistance, such formal descriptions of flight‐related tasks and processes can describe what constitutes normative performance.…”

Section: Introductionmentioning

confidence: 99%

A Neuroadaptive Cognitive Model for Dealing With Uncertainty in Tracing Pilots' Cognitive State

Klaproth

Halbrügge

Krol³

et al. 2020

Topics in Cognitive Science

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A model‐based approach for cognitive assistance is proposed to keep track of pilots' changing demands in dynamic situations. Based on model‐tracing with flight deck interactions and EEG recordings, the model is able to represent individual pilots' behavior in response to flight deck alerts. As a first application of the concept, an ACT‐R cognitive model is created using data from an empirical flight simulator study on neurophysiological signals of missed acoustic alerts. Results show that uncertainty of individual behavior representation can be significantly reduced by combining cognitive modeling with EEG data. Implications for cognitive assistance in aviation are discussed.

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Section: Introductionmentioning

confidence: 99%

A Neuroadaptive Cognitive Model for Dealing With Uncertainty in Tracing Pilots' Cognitive State

Klaproth

Halbrügge

Krol³

et al. 2020

Topics in Cognitive Science

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“…That is, IMC‐day was expected to yield greater RMSEs than IMC‐night because of lower saliency of symbology against the high brightness background ( H1‐2 ). In addition, as the required information for a pilot was different for each leg of flight, pilot attention patterns were expected to vary by leg, leading to a different profile of flight path tracking (Byrne et al, 2004). Pilots were expected to produce higher RMSE values in Legs 1 and 4 than in Legs 2 and 3 ( H1‐3 ) because cognitive load might be higher in Leg 1 because of the need to manipulate instruments and in Leg 4 because of landing.…”

Section: Methodsmentioning

confidence: 99%

Examining the Effects of Conformal Terrain Features in Advanced Head‐Up Displays on Flight Performance and Pilot Situation Awareness

Kim

Kaber

2012

Hum Ftrs & Erg Mfg Svc

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Synthetic vision systems (SVS) render terrain features for pilots through cockpit displays using a GPS database and three-dimensional graphical models. Enhanced vision systems (EVS) present infrared imagery of terrain using a forward-looking sensor in the nose of an aircraft. The ultimate goal of SVS and EVS technologies is to support pilots in achieving safety under low-visibility and night conditions comparable to clear, day conditions. This study assessed pilot performance and situation awareness (SA) effects of SVS and EVS imagery in an advanced head-up display (HUD) during a simulated landing approach under instrument meteorological conditions. Videos of the landing with various HUD configurations were presented to eight pilots with a superimposed tracking task. The independent variables included four HUD feature configurations (baseline [no terrain imagery], SVS, EVS, and a combination of SVS and EVS), two visibility conditions, and four legs of the flight. Results indicated that SVS increased overall SA but degraded flight path control performance because of visual confusion with other display features. EVS increased flight path control accuracy but decreased system (aircraft) awareness because of visual distractions. The combination of SVS and EVS generated offsetting effects. Display configurations did not affect pilot spatial awareness. Flight performance was not different among phases of the approach, but levels and types of pilot SA did vary from leg to leg. These results are applicable to development of adaptive HUD features to support pilot performance. They support the use of multidimensional measures of SA for insight on pilot information processing with advanced aviation displays. C 2012 Wiley Periodicals, Inc.

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“…ACT-R has seen many applications in aviation (e.g., Taatgen, Huss, Dickison, & Anderson, 2008;Somers & West, 2013;Schoppek & Boehm-Davis, 2004;Byrne et al, 2004) and has also been used for research on incorporating perspective-taking within a robotic teammate (Kennedy et al, 2008). Most studies using ACT-R rely on laboratory-like simulations and do not account for real-time and real-life human behavior.…”

Section: Cognitive Architecturesmentioning

confidence: 99%

Cognitive Modeling of Anticipation: Unsupervised Learning and Symbolic Modeling of Pilots' Mental Representations

Blum

Klaproth

Rußwinkel

2022

Topics in Cognitive Science

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The ability to anticipate team members' actions enables joint action towards a common goal. Task knowledge and mental simulation allow for anticipating other agents' actions and for making inferences about their underlying mental representations. In human-AI teams, providing AI agents with anticipatory mechanisms can facilitate collaboration and successful execution of joint action. This paper presents a computational cognitive model demonstrating mental simulation of operators' mental models of a situation and anticipation of their behavior. The work proposes two successive steps: (1) A hierarchical cluster algorithm is applied to recognize patterns of behavior among pilots. These behavioral clusters are used to derive commonalities in situation models from empirical data (N = 13 pilots).(2) An ACT-R (adaptive control of thought -rational) cognitive model is implemented to mentally simulate different possible outcomes of action decisions and timing of a pilot. model tracing of ACT-R allows following up on operators' individual actions. Two models are implemented using the symbolic representations of ACT-R: one simulating normative behavior and the other by simulating individual differences and using subsymbolic learning. Model performance is analyzed by a comparison of both models. Results indicate the improved performance of the individual differences over the normative

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A closed-loop, ACT-R approach to modeling approach and landing with and without synthetic vision system (SVS) technology

Cited by 4 publications

References 0 publications

A Neuroadaptive Cognitive Model for Dealing With Uncertainty in Tracing Pilots' Cognitive State

A Neuroadaptive Cognitive Model for Dealing With Uncertainty in Tracing Pilots' Cognitive State

Examining the Effects of Conformal Terrain Features in Advanced Head‐Up Displays on Flight Performance and Pilot Situation Awareness

Cognitive Modeling of Anticipation: Unsupervised Learning and Symbolic Modeling of Pilots' Mental Representations

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