FIPRED: A Study of Predictive Automated Displays for Wildfire Fighting Management

Predictor displays are a form of automation that have been shown to provide a notable benefit in many environments and are applied to wildfire suppression in the present study. 22 participants were recruited to participate in a wildfire prediction study in which they predicted the fire trajectory based on the automated predictor and their interpretation of the raw data. In all scenarios, a large predictor benefit was observed, and in four of six scenarios, significant signs of automation bias were found, following an erroneous automated prediction. Participants performed significantly worse when the raw data influences on the trajectory were removed in a control study, signaling the value of such data in calibrating dependence on the predictor. The FIPRED display was beneficial to participants, improving their ability to predict the future position of the fire. However, the automation bias indicated that participants may have over-relied on the automated assistance.

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Publication Details

Journal
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Published
2025-08-31
DOI
https://doi.org/10.1177/10711813251364799
Primary Topic
Evacuation and Crowd Dynamics
Type
article
Field-Weighted Citation Impact
0.00
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article

FIPRED: A Study of Predictive Automated Displays for Wildfire Fighting Management

Chris Wickens, Robert Spenceley, Bianca de Toledo Piza
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Evacuation and Crowd Dynamics
article

FIPRED: A Study of Predictive Automated Displays for Wildfire Fighting Management

Chris Wickens, Robert Spenceley, Bianca de Toledo Piza
article en

Abstract

Predictor displays are a form of automation that have been shown to provide a notable benefit in many environments and are applied to wildfire suppression in the present study. 22 participants were recruited to participate in a wildfire prediction study in which they predicted the fire trajectory based on the automated predictor and their interpretation of the raw data. In all scenarios, a large predictor benefit was observed, and in four of six scenarios, significant signs of automation bias were found, following an erroneous automated prediction. Participants performed significantly worse when the raw data influences on the trajectory were removed in a control study, signaling the value of such data in calibrating dependence on the predictor. The FIPRED display was beneficial to participants, improving their ability to predict the future position of the fire. However, the automation bias indicated that participants may have over-relied on the automated assistance.

Proceedings of the Human Factors and Ergonomics Society Annual MeetingVol. 69(1)
University of Wisconsin–Madison (US), Colorado State University (US)
Openalex Percentile: Top 72%
Evacuation and Crowd Dynamics
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FIPRED: A Study of Predictive Automated Displays for Wildfire Fighting Management — Chris Wickens, Robert Spenceley, et al. · Proceedings of the Human Factors and Ergonomics Society Annual Meeting (2025) | TGRS Research Map | TGRS