Peripheral vision in real-world tasks: A systematic review
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13423_2022_Article_2117.pdf
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1.28 MB
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Author(s)
Vater, Christian
Wolfe, Benjamin
Rosenholtz, Ruth
Date Issued
May 2022
Journal
Psychonomic Bulletin & Review
Publisher
Springer Science and Business Media LLC
Citation
Vater, Christian, Wolfe, Benjamin and Rosenholtz, Ruth. 2022. "Peripheral vision in real-world tasks: A systematic review."
Version
Final published version
Abstract
Abstract
Peripheral vision is fundamental for many real-world tasks, including walking, driving, and aviation. Nonetheless, there has been no effort to connect these applied literatures to research in peripheral vision in basic vision science or sports science. To close this gap, we analyzed 60 relevant papers, chosen according to objective criteria. Applied research, with its real-world time constraints, complex stimuli, and performance measures, reveals new functions of peripheral vision. Peripheral vision is used to monitor the environment (e.g., road edges, traffic signs, or malfunctioning lights), in ways that differ from basic research. Applied research uncovers new actions that one can perform solely with peripheral vision (e.g., steering a car, climbing stairs). An important use of peripheral vision is that it helps compare the position of one’s body/vehicle to objects in the world. In addition, many real-world tasks require multitasking, and the fact that peripheral vision provides degraded but useful information means that tradeoffs are common in deciding whether to use peripheral vision or move one’s eyes. These tradeoffs are strongly influenced by factors like expertise, age, distraction, emotional state, task importance, and what the observer already knows. These tradeoffs make it hard to infer from eye movements alone what information is gathered from peripheral vision and what tasks we can do without it. Finally, we recommend three ways in which basic, sport, and applied science can benefit each other’s methodology, furthering our understanding of peripheral vision more generally.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.3758/s13423-022-02117-w
