Model based Analysis of Two-Alternative Decision Errors in a Videopanorama-based Remote Control Tower Work Position

Kurzfassung

Remote Control Tower operation (RTO) for airport ground traffic control without the need for a local physical tower building is presently in the transition phase from research to the prototype with testing in the operational environment(e.g.[1][2][3][4][5]). State of the art technology is based on a digital videopanorama with HD-format camera technology, e.g. 4 - 5 cameras (focal width of 8 – 13 mm) with 45 - 60° vertical field-of-view for a 180° - 200° horizontal panorama. It is presently limited by a visual resolution of typically 1/30° per pixel under good visibility conditions (= 2 arcmin, about half as good as the resolution of the human eye). This is the Nyquist limit of the modulation transfer function which typically shows a significant contrast reduction (dependent on the quality of the optical system) down to 10 - 20% of the maximum value (see also the spatial standard observer model of [7]). Initial analysis of a first validation experiment including aircraft maneuver observation in the control zone during aerodrome circling (left Figure) has shown that a specific subset of two-alternative decision tasks [5] as part of a larger set of operationally relevant tasks of controllers [4] exhibit a significant performance decrease of the remote as compared to the conventional tower work position (RTO vs. TWR-CWP). This RTO-CWP deficit was measured despite the use of a manually controlled pan-tilt zoom camera (analog PTZ with PAL TV-resolution, selectable zoom factor setting Z = 2 - 16, viewing angle 26° - 3°) which was expected to compensate for the videopanorama resolution and corresponding detectability limitations. The present analysis includes a model based approach and extends the initial data evaluation of two-alternative decision tasks [5] which was based on a subset of the complete two-alternative data. The results motivate the introduction of additional RTO-automation functions in order to reduce the increase of time pressure (TP) originating from the requirement of PTZ-usage as compensation of the low panorama resolution. As part of the passive shadow-mode test [3,4,5] eight air-traffic controllers observed various flight-maneuvers during airport circling (left Figure), like bank angle and altitude changes, and gear-up / gear-down situations. The response matrix of the two-alternative decision tasks as obtained by measuring the hit (H) and false alarm (FA) rates when reporting on the observation of, e.g. gear-up vs. gear-down situation during approach, yielded a significant increase of decision errors under RTO-CWP conditions, when interpreting non-answers as errors. As a hypothesis the significant increase of RTO-CWP errors is related to an increase of time pressure TP = required time / time available, with limited time available Ta = 10 s. For the specific two-alternative decision tasks Ta was mostly sufficient for TWR-CWP decision making, however apparently much more often not so for RTO-CWP. We use the Perceptual Control Theory (PCT) based Time Pressure (TP) model of Hendy et.al [6] for deriving an initial estimate of the two exponential model parameters based on the TWR and RTO decision errors, including the non-answers as erroneous decisions (see right figure). This result has to be treated as an initial guess only because it relies on the two data points for TWR and RTO. and it indicates, however the direction for improved future experiments with varying TP. Additional information is obtained by means of Bayes inference and detection theory with graphical presentation through ROC-curves. The latter method allows for separating discriminability from response bias and was previously successfully used for deriving a video framerate requirement that minimizes prediction errors in a simulated landing scenario (e.g. [8]). Left Figure: GPS-track of test aircraft showing aerodrome circling with events like bank angle changes (A), altitude changes (D), and gear-out/in (H), indicating TWR/ATC and remote/RTC decision locations on the trajectory. Vertical lines end at average airport height 319 m. Observers at tower position of ca. (0,0,350 m) with 200° RTO-panorama viewing north. Right Figure: Example of time pressure model based analysis of decision errors. Estimate of time pressure (TP) model parameters with response times Tr arbitrarily selected as Tr(TWR) :=5 s < Ta, Tr(RTO) := 20 s > Ta. When interpreting non-answers as errors (worst case assumption) the present analysis provides an estimate of the increase of decision errors under RTO conditions as quantified by a discriminability (d’-) decrease by a factor of up to 3, as compared to the conventional TWR-CWP. The Bayes inference analysis based on the same measured H and FA a-priori (conditional) probabilities provides a corresponding increase for risk of false decisions. It is significant also when assuming a chance interpretation of non-answers (i.e. only 50% erroneous if there were sufficient time available for RTO-conditions). The TWR-RTO difference was observed A/C maneuvers without altitude change because for altitude related tasks operators selected the radar information. The perceptual control theory with time pressure as proposed explanation for the non-answer and decision error-increase respectively leads to the hypothesis that suitable RTO-automation such as augmentation of the far view by superimposition of approach radar information for aircraft position cueing and automatic zoom camera tracking (e.g. via image processing or ADS-B position data fusion) together with improved operator training might eliminate the observed RTO-CWP performance deficit. A corresponding investigation is presently underway. [1] M. Schmidt, M. Rudolph, B. Werther, N. Fürstenau, “Development of an Augmented Vision Videopanorama Human-Machine Interface for Remote Airport Tower Operation”: Proc. HCII2007 Beijing, Springer Lecture Notes Computer Science 4558, 2007, 1119-1128. [2] N. Fürstenau, M.,Schmidt, M.Rudolph, C.Möhlenbrink, A.Papenfuß, S. Kaltenhäuser: “Steps Towards the Virtual Tower: Remote Airport Traffic Control Center (RAiCe)”, Proc. EIWAC 2009, ENRI Int. Workshop on ATM & CNS, Tokyo, 5.-6.3.2009, pp. 67-76 [3] SESAR-JU Project 06.09.03: “Remote Provision of ATS to a Single Aerodrome - Validation Report”, edition 00.01.02, www.sesarju.eu [4] M. Friedrich, C. Möhlenbrink: “Which Data provide the best insight? A field trial for validating a remote tower operation concept”, Proc. 10th USA/Europe ATM Seminar, Chicago,IL, USA June 10 – 13 (2013) [5] Fürstenau. N., Friedrich, M., Mittendorf, M., Schmidt, M., Rudolph, M.: “Discriminability of Flight Maneuvers and Risk of False Decisions Derived from Dual Choice Decision Errors in a Videopanorama-based Remote Tower Work Position”. Proc. HCI 2013: Lecture Notes Artificial Intelligence, vol.8020 pp.105-114, Springer, Heidelberg, New York (2013) [6] K.C. Hendy, P.S.E. Farrell, K.P. East, “An Information-Processing Model of Operator Stress and Performance”. In: P.A. Hancock, P.A. Desmond (Eds.), “Stress, Workload, and Fatigue”.Lawrence Erlbaum, Mahwah/ N.J. [7] A.B. Watson, C.V. Ramirez, and E.Salud, “Predicting visibility of aircraft”, PLoS ONE. 2009; 4(5): e5594. Pub-lished online 2009 May 20. doi: 10.1371/journal.pone.0005594 [8] N. Fürstenau, M. Mittendorf, S. Ellis: “Remote Towers: Videopanorama Frame Rate Requirements derived from Visual Discrimination of Deceleration during Simulated Aircraft Landing”. Dirk Schäfer (Ed.) Proc. 2nd SESAR Innovation Days (2012), Eurocontrol, Braunschweig 27th-29th , ISBN 978-2-87497-024-5