Coadaptive aiding and automation enhance operator performance.
OBJECTIVE
In this work, we expand on the theory of adaptive aiding by measuring the effectiveness of coadaptive aiding, wherein we explicitly allow for both system and user to adapt to each other.


BACKGROUND
Adaptive aiding driven by psychophysiological monitoring has been demonstrated to be a highly effective means of controlling task allocation and system functioning. Psychophysiological monitoring is uniquely well suited for coadaptation, as malleable brain activity may be used as a continuous input to the adaptive system.


METHODS
To establish the efficacy of the coadaptive system, physiological activation of adaptation was directly compared with manual activation or no activation of the same automation and cuing systems. We used interface adaptations and automation that are plausible for real-world operations, presented in the context of a multi-remotely piloted aircraft control simulation. Each participant completed 3 days of testing during 1 week. Performance was assessed via proportion of targets successfully engaged.


RESULTS
In the first 2 days of testing, there were no significant differences in performance between the conditions. However, in the third session, physiological adaptation produced the highest performance.


CONCLUSIONS
By extending the data collection across multiple days, we offered enough time and repeated experience for user adaptation as well as online system adaptation, hence demonstrating coadaptive aiding.


CONCLUSIONS
The results of this work may be employed to implement more effective adaptive workstations in a variety of work domains.
Air Force Research Laboratory, 2510 Fifth Street B840, Wright-Patterson AFB, OH 45433, USA. james.christensen@wpafb.af.mil
James C
JC
Christensen
Justin R
JR
Estepp
D000222:Adaptation, Physiological / Q000502:physiology*; D000328:Adult; D001331:Automation; D001359:Aviation; D005260:Female; D006801:Humans; D008297:Male; D008328:Man-Machine Systems; D009473:Neuronal Plasticity / Q000502:physiology; D013647:Task Performance and Analysis; D014584:User-Computer Interface; D016526:Workload; D055815:Young Adult