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Automation surprises in commercial aviation
Published in Michael A. Vidulich, Pamela S. Tsang, John Flach, Advances in Aviation Psychology, Volume 2, 2017
The capabilities of automated flight systems increased rapidly following the introduction of the electronic autopilot in the 1940s. In normal operations, the automated flight system of the modern airliner can now control nearly all functions required for flight. The effect of increased automation has been largely positive, greatly reducing errors due to pilot fatigue and allowing consistent precise navigation and performance. However, automation has given rise to new problems caused by faulty interactions between the pilot and the autoflight system (AFS). This class of problems has been variously termed lack of mode awareness (Javaux & De Keyser, 1998), mode confusion (Degani, Shafto, & Kirlik, 1999), and automation surprise (Wiener & Curry, 1980; Sarter, Woods, & Billings, 1997, Woods & Sarter, 2000; Burki-Cohen, 2010). In these cases, the flight crew expects the automation to command one behavior and is surprised when it commands another. Automation surprise may result from undetected failures in aircraft sensors or other systems. Automation surprise also may result from pilots having an inadequate or mistaken “mental model” of the machine’s behavior in the operational environment (Sarter & Woods, 1995). In addition, automation surprise may result from a problematic interface that does not provide adequate information about the status of the machine (Norman, 1990; Feary et al., 1998; Degani et al., 1999).
The 1940s and Onward
Published in Sidney Dekker, Foundations of Safety Science, 2019
An automation surprise can then be defined as the end result of a deviation between expectation and actual system behavior that is only discovered after the crew notices strange or unexpected behavior and that may already have led to serious consequences by that time (Dekker, 2014) (Table 5.2).
A Novel Cooperation-Guided Warning of Invisible Danger from AR-HUD to Enhance Driver’s Perception
Published in International Journal of Human–Computer Interaction, 2023
Fang You, Jun Zhang, Jie Zhang, Lian Shen, Weixuan Fang, Wei Cui, Jianmin Wang
Trust is pivotal in autonomous driving. When the autonomous driving system does something that does not meet the driver’s expectations, the automation surprise phenomenon can undermine humans’ trust in the vehicle. In Case 2, whether an intelligent system could decrease automation surprise and improve trust by displaying other vehicles’ intentions through an AR-HUD was explored. The design method proposed by this study was also adopted in the design of this cooperation interface that displays different stages (ie, information acquisition, information analysis, decision-making, and action implementation) to measure the impact on human drivers (see Table 1 and Figure 3).