Active Control versus Passive Monitoring in Air Traffic Control

emerging Updated: 2026-06-07
air-traffic-control supervisory-control passive-monitoring out-of-the-loop conflict-detection mental-workload vigilance free-flight situational-awareness remote-operations

Active Control versus Passive Monitoring in Air Traffic Control

Status: emerging
Last updated: 2026-06-07
Sources: 001872001775870421.Pdf
Tags: [air-traffic-control, supervisory-control, passive-monitoring, out-of-the-loop, conflict-detection, mental-workload, vigilance, free-flight, situational-awareness, remote-operations]

Summary

Proposals for future air traffic management such as Free Flight shift responsibility for keeping aircraft apart from ground controllers to pilots, changing the air traffic controller's (ATCo) role from active control to passive monitoring. Metzger and Parasuraman (2001) tested what this costs by having controllers run the same simulated traffic either actively or as monitors, under moderate and high density. Passive monitoring and high traffic each degraded the timeliness of conflict detection, and under high traffic controllers took almost twice as long to detect a conflict when monitoring as when controlling. The study gives direct empirical support to keeping separation authority with the human operator rather than relegating that operator to a monitor — the central design question for any remote or supervisory control centre.

Body

Context

Metzger and Parasuraman (2001) report a medium-fidelity ATC simulator experiment comparing active control against passive monitoring, crossed with moderate versus high traffic density, in a 2×2 within-subject design (14 certified controllers). The lens is supervisory control: the authors frame the monitoring role created by advanced Free Flight as functionally equivalent to the out-of-the-loop state produced by high-level automation, since both strip decision authority from the operator (PDF p. 3, orig. p. 521). Within this knowledge base the article is the air-traffic-control anchor for a recurring theme across domains — that removing the operator from the control loop degrades the operator's ability to step back in. It is the ATC counterpart to the maritime out-of-the-loop and transparency work in Human In The Loop Automation Transparency and to the cross-domain workload and situational-awareness synthesis in Multi Ship Remote Operations Workload Sa.

Key Points

The design isolates the effect of control type. Two traffic scenarios (averaging 11 aircraft for moderate, 17 for high density) were reused for active and monitoring conditions, with sector boundaries, routes, call signs, and way points rotated so that performance differences could be attributed to control type rather than to a particular conflict geometry. Under active control, controllers both detected and resolved scripted potential conflicts by issuing clearances; under passive monitoring they only acknowledged detections by clicking a button, mirroring the controller's role under mature Free Flight (PDF pp. 3–4, orig. pp. 521–522).

Detection timeliness, not detection rate, carried the control effect. The percentage of missed potential conflicts was driven by traffic density (65.18% missed under high vs. 14.73% under moderate) and event type, with no significant difference between monitoring and active control (PDF p. 5, orig. p. 523). Advanced notification time — how early a conflict was flagged — showed the predicted main effect of control: controllers detected potential conflicts significantly earlier under active control (250.85 s) than under passive monitoring (197.12 s), and earlier under moderate than high density (PDF p. 5, orig. p. 523). The decisive result is the interaction: under high traffic it took controllers almost two minutes (117.51 s) longer to detect a conflict when monitoring than when controlling, whereas under moderate traffic there was no cost (PDF p. 6, orig. p. 524).

Memory and workload findings complete the picture. Controllers recalled aircraft altitude better under active control (16.67%) than under passive monitoring (6.25%, a marginal difference), while lateral-position recall was poor (<30%) and unaffected by control type (PDF p. 7, orig. p. 525). Subjective (NASA-TLX) and objective measures showed higher mental workload under high traffic, but control type had no significant effect on workload — the authors suggest active control's lower monitoring demand was offset by the added task of conflict resolution (PDF pp. 7–8, orig. pp. 525–526).

Conclusion

Metzger and Parasuraman (2001) conclude that passive monitoring reproduces the out-of-the-loop performance problem associated with high-level decision automation: when authority for separation is taken away, the operator is slower to detect the conflicts they may later be required to resolve, and the deficit is largest precisely under the dense traffic that Free Flight is meant to accommodate. Because denser airspace leaves less time to recover from emergencies, a monitor who needs more time to detect a conflict erodes the safety margin. The results support more recent proposals to keep separation authority on the ground with an actively engaged controller, supplemented by conflict-detection and resolution aids, rather than the original RTCA vision of the controller as passive monitor.

References

Metzger, U. and Parasuraman, R. (2001) 'The Role of the Air Traffic Controller in Future Air Traffic Management: An Empirical Study of Active Control versus Passive Monitoring', Human Factors, 43(4), pp. 519–528. doi: 10.1518/001872001775870421. metzger2001role

Endsley, M.R. and Kiris, E.O. (1995) 'The out-of-the-loop performance problem and level of control in automation', Human Factors, 37(2), pp. 381–394. To be validated.

Galster, S.M., Duley, J.A., Masalonis, A.J. and Parasuraman, R. (2001) 'Air traffic controller performance and workload under mature free flight: Conflict detection and resolution of aircraft self-separation', International Journal of Aviation Psychology, 11(1), pp. 71–93. To be validated.

Parasuraman, R. and Riley, V. (1997) 'Humans and Automation: Use, Misuse, Disuse, Abuse', Human Factors, 39(2), pp. 230–253. doi: 10.1518/001872097778543886. parasuraman1997humans

Open Questions

  • The negative effects were measured under "relatively novel" unstructured-airspace conditions with controllers unaccustomed to them. Metzger and Parasuraman note that learning and prior experience with unstructured airspace (e.g. some military controllers) might reduce the monitoring deficit. How much is trainable remains open.
  • Control type did not affect mental workload here, possibly because workload was high across all conditions (a ceiling/data-limited effect). Whether passive monitoring imposes lower workload at lower overall load is unresolved.
  • The equivalence drawn between passive monitoring and high-level automation rests on the shared loss of decision authority. How closely the human-monitoring-human case maps onto the human-monitoring-automation case (e.g. trust dynamics) is asserted rather than tested.