Automation Reliability in Unmanned Aerial Vehicle Control: A Reliance-Compliance Model of Automation Dependence in High Workload

By Stephen R. Dixon, C. Wickens. Hum. Factors, 2006

317 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Social Psychology

View Paper: https://www.semanticscholar.org/paper/eea5e05ed52be43619db9eda460409777f4cd4b1

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Citations in the corpus

Trust and Reliance on an Automated Combat Identification System (2009, background): “Reliance refers to the user’s responding as if there is noise in the world given noise feedback ( Dixon & Wickens, 2006; Dixon, Wickens, & McCarley, 2007; Meyer, 2001, 2004).”
Impact of robot failures and feedback on real-time trust (2013, methodology): “IN T RO D U C T I O N During an operator s interaction with an autonomous system, a key issue is how the operator uses the available autonomy levels, often referred to as the control allocation strategy [1].”
Understanding human management of automation errors (2013, background): “Similarly, although error type has a signiﬁcant impact on error management under conditions of high workload, under low workload error management is at ceiling and no difference based on error type exists (Dixon and Wickens 2006).”
On the Independence of Compliance and Reliance: Are Automation False Alarms Worse Than Misses? (2007, background): “Dixon and Wickens (2006) reported data partially consistent with this assertion.”
Are Well-Calibrated Users Effective Users? Associations Between Calibration of Trust and Performance on an Automation-Aided Task (2015, unknown): “This design provides us with greater experimental control and is consistent with past research (e.g., Dixon & Wickens, 2006; Dixon, Wickens, & McCarley, 2007; Rice, 2009).”
The Role of Trust as a Mediator Between System Characteristics and Response Behaviors (2015, background): “Researchers have elaborated on the underlying processes of trust by describing compliance and reliance behaviors in response to systems that are either false alarm prone (FP) or miss prone (MP; Dixon et al., 2007). Rice (2009) concluded that a multiprocess model of trust provided the best explanatio”
Humans: Still Vital After All These Years of Automation (2008, methodology): “But with Stage 1 to 2 automation, mistrust imposes qualitatively different effects that have been modeled by the cognitive concepts of reliance and compliance as we elaborate in what follows (Dixon & Wickens, 2006; Meyer, 2004).”
Complacency and Automation Bias in the Use of Imperfect Automation (2015, background): “This situation is known as overcompliance and typically includes incorrect, unnecessary actions performed on the system (an HAI error of commission; Dixon & Wickens, 2006).”