How do pedestrians distribute their visual attention when walking through a parking garage? An eye-tracking study

Journal Article (2021)
Author(s)

JCF Winter (TU Delft - Human-Robot Interaction)

P. Bazilinskyy (TU Delft - Human-Robot Interaction)

Dale Wesdorp (Student TU Delft)

Valerie de Vlam (Student TU Delft)

Belle Hopmans (Student TU Delft)

Just Visscher (Student TU Delft)

D Dodou (TU Delft - Medical Instruments & Bio-Inspired Technology)

Research Group
Human-Robot Interaction
Copyright
© 2021 J.C.F. de Winter, P. Bazilinskyy, Dale Wesdorp, Valerie de Vlam, Belle Hopmans, Just Visscher, D. Dodou
DOI related publication
https://doi.org/10.1080/00140139.2020.1862310
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 J.C.F. de Winter, P. Bazilinskyy, Dale Wesdorp, Valerie de Vlam, Belle Hopmans, Just Visscher, D. Dodou
Research Group
Human-Robot Interaction
Issue number
6
Volume number
64
Pages (from-to)
793-805
Reuse Rights

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Abstract

We examined what pedestrians look at when walking through a parking garage. Thirty-six participants walked a short route in a parking garage while their eye movements and head rotations were recorded with a Tobii Pro Glasses 2 eye-tracker. The participants’ fixations were then classified into 14 areas of interest. The results showed that pedestrians often looked at the back (20.0%), side (7.5%), and front (4.2%) of parked cars, and at approaching cars (8.8%). Much attention was also paid to the ground (20.1%). The wheels of cars (6.8%) and the driver in approaching cars (3.2%) received attention as well. In conclusion, this study showed that eye movements are largely functional in the sense that they appear to assist in safe navigation through the parking garage. Pedestrians look at a variety of sides and features of the car, suggesting that displays on future automated cars should be omnidirectionally visible. Practitioner summary: This study measured where pedestrians look when walking through a parking garage. It was found that the back, side, and wheels of cars attract considerable attention. This knowledge may be important for the development of automated cars that feature so-called external human-machine interfaces (eHMIs).