Designing automation for human use: empirical studies and quantitative models

By Raja Parasuraman. Ergonomics, 2000

310 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Social Psychology

View Paper: https://www.semanticscholar.org/paper/035e62d7c1954eb7e893d12a7caa3aa0785f9018

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Citations in the corpus

Automated Planning for Peer-to-peer Teaming and its Evaluation in Remote Human-Robot Interaction (2015, background): “it is well known that it can have both positive and negative effects on human performance [2].”
Complacency and Bias in Human Use of Automation: An Attentional Integration (2010, background): “Parasuraman et al. (1993) found that in the experimental group that exhibited this effect, the mean detection rate of automation failures was quite low, 33%. But there was considerable variability around this mean, and as many as half of the participants in the group did not detect any malfunctions ”
Designing for Flexible Interaction Between Humans and Automation: Delegation Interfaces for Supervisory Control (2007, background): “Good system and interface design, improved feedback to the user about automation (Nikolic & Sarter, 2000; Parasuraman, 2000), increased reporting requirements, and good hiring and training practices can all serve to reduce unpredictability.”
RADAR - A Proactive Decision Support System for Human-in-the-Loop Planning (2017, background): “Later, in the study of mental workload and situational awareness of humans performing alongside automation software, (Parasuraman 2000) separates automation into four parts- Information Acquisition, Information Analysis, Decision Selection and Action Implementation (see Figure 2).”
Investigation of Behavioral Adaptation to Lane Departure Warnings (2002, background): “Alternatively, an operator who trusts the system too much may become complacent and fail to override the system when it is faulty, a phenomenon known as automation complacency (14).”
Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy (2019, methodology): “To assist leaders develop more sophisticated automation strategies several quantitative and qualitative models have been developed (Parasuraman, 2000).”
A model for types and levels of human interaction with automation (2000, methodology): “Several computational models of human-automation interaction have been put forward very recently, including models based on expected value statistics [37], [78], task-load models [79], cognitive-system models [80], and a model based on state-transition networks [81] (for a recent review of these mod”
Familiarization with a Forward Collision Warning on driving simulator: cost and benefit on driversystem interactions and trust (2010, background): “However, alarm suppression may delay drivers’ reactions and decrease the perceived effectiveness of the system (Parasuraman, 2000).”
Automation and Accountability in Decision Support System Interface Design (2006, background): “The accident investigation revealed nothing was wrong with the system software or hardware, but that the accident was caused by inadequate and overly complex display of information to the controllers (van den Hoven, 1994).”