Human vs machine strategies: the impact of strategic conformance on operator workload, performance and automation acceptance

The MUFASA project simulated "automation performance" using unrecognizable replays of a given controller's own previous performance. Using a prototype air traffic control interface, it explored with operational air traffic controllers the interactive effects of traffic complexity, level of automation and "strategic conformance" (defined as the match between human and machine solution strategy) on a number of dependent measures. A main effect of conformance was observed on acceptance, agreement, and response time. Conformal advisories were accepted more often, rated higher, and responded to faster than were non-conformal advisories. Complexity, on the other hand, showed a main effect on acceptance, agreement and workload: all three increased with complexity. In the end, one result stood out in particular: 23.8% of conformal advisories were rejected by controllers. How could it be that controllers, in effect, disagreed with their very own solutions roughly one quarter of the time? The project is currently exploring this and other related issues through extended human-in-the-loop simulations.