Using Situational Awareness and Situative Criticality for Adaptive Planning Assistance in MUM-T Missions

This study examines the effect of adaptive assistance in online mission planning for military aircraft pilots in Manned-Unmanned-Teaming (MUM-T) missions. We evaluated two adaptive approaches to select from three levels of assistance in a cockpit simulator experiment. Both approaches used the criticality of the situation to choose an assistance level, with one approach additionally integrating an eye-tracking-based measure of Situational Awareness (SA). Based on these triggers, the adaptive system used different levels of assistance for mission planning support. We compared these two adaptive conditions to a baseline setup without assistance and evaluated performance, workload, usability, and subjective SA. Performance was assessed by flight data and mission completion times, while workload, usability, and SA were assessed with standard questionnaires. Both assistance systems exceeded the non-assisted baseline in terms of mission time, workload management, SA, and usability. Pilots supported by adaptive assistance integrating both, criticality, and SA, showed improvements in subjective SA over the criticality-only-condition while demonstrating faster mission completion. The findings suggest that adaptive assistance, particularly when incorporating SA, can enhance pilot performance in MUM-T operations.

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Publication Details

Published
2024-10-06
DOI
https://doi.org/10.1109/smc54092.2024.10832039
Primary Topic
AI-based Problem Solving and Planning
Type
article
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article

Using Situational Awareness and Situative Criticality for Adaptive Planning Assistance in MUM-T Missions

Axel Schulte, Simon Schwerd, Julian Bautz
AI-based Problem Solving and Planning
article

Using Situational Awareness and Situative Criticality for Adaptive Planning Assistance in MUM-T Missions

Axel Schulte, Simon Schwerd, Julian Bautz
article en

Abstract

This study examines the effect of adaptive assistance in online mission planning for military aircraft pilots in Manned-Unmanned-Teaming (MUM-T) missions. We evaluated two adaptive approaches to select from three levels of assistance in a cockpit simulator experiment. Both approaches used the criticality of the situation to choose an assistance level, with one approach additionally integrating an eye-tracking-based measure of Situational Awareness (SA). Based on these triggers, the adaptive system used different levels of assistance for mission planning support. We compared these two adaptive conditions to a baseline setup without assistance and evaluated performance, workload, usability, and subjective SA. Performance was assessed by flight data and mission completion times, while workload, usability, and SA were assessed with standard questionnaires. Both assistance systems exceeded the non-assisted baseline in terms of mission time, workload management, SA, and usability. Pilots supported by adaptive assistance integrating both, criticality, and SA, showed improvements in subjective SA over the criticality-only-condition while demonstrating faster mission completion. The findings suggest that adaptive assistance, particularly when incorporating SA, can enhance pilot performance in MUM-T operations.

Universität der Bundeswehr München (DE)
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AI-based Problem Solving and Planning
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