The Duration of Automation Bias in a Realistic Setting

Abstract

Whereas in most studies conducted previously the effect of automation bias has been investigated in terms of an instantaneous decision, this study is aimed at quantifying its duration. Automation bias is modeled as a stochastic process using a unimodal log-log probability distribution. To validate the model, an experiment using an Airbus A320 fixed-base flight simulator with a malfunction on the auto-throttle was executed with 35 licensed pilots. The effect of pilot experience is investigated; results show that less experienced pilots are on average less sensitive to automation bias but have more variation in performance than more experienced pilots.