Assessing drivers' visual-motor coordination using eye tracking, GNSS and GIS: a spatial turn in driving psychology

Sun, Q, Xia, J, Nadarajah, N, Falkmer, T, Foster, J and Lee, H 2016, 'Assessing drivers' visual-motor coordination using eye tracking, GNSS and GIS: a spatial turn in driving psychology', Journal of Spatial Science, vol. 61, no. 2, pp. 299-316.


Document type: Journal Article
Collection: Journal Articles

Title Assessing drivers' visual-motor coordination using eye tracking, GNSS and GIS: a spatial turn in driving psychology
Author(s) Sun, Q
Xia, J
Nadarajah, N
Falkmer, T
Foster, J
Lee, H
Year 2016
Journal name Journal of Spatial Science
Volume number 61
Issue number 2
Start page 299
End page 316
Total pages 18
Publisher Taylor and Francis Asia Pacific
Abstract Vehicle-driving in real traffic can be considered as a human-machine system involving not only the attribute of the vehicle movement but also the human visual perception, cognition and motion of the driver. The study of driving behaviours, therefore, would integrate information related to driver psychology, vehicle dynamics and road information in order to tackle research questions concerning driving safety. This paper describes a conceptual framework and an integrated GIS data model of a visual-motor coordination model (VMCM) to investigate drivers' driving behaviour via the combination of vision tracking and vehicle positioning. The eye tracker recorded eye fixations and duration on video images to exhibit the driver's visual search pattern and the traffic scenes. Real-time kinematic (RTK) post-processing of multi-GNSS (global navigation satellite system) tracking generated the vehicle movement trajectory at centimeter-level accuracy, which encompasses precise lateral positioning and speed control parameters of driving behaviours. The eye fixation data were then geocoded and linked to the vehicle movement trajectory to represent the VMCM on the GIS platform. An implementation prototype of the framework and the VMCM for a study of older drivers is presented in this paper. The spatial-temporal visualisation and statistical analysis based on the VMCM data-set allow for a greater insight into the inherent variability of older drivers' visual search and motor behaviours. The research framework has demonstrated a discriminant and ecologically valid approach in driving behaviour assessment, which can also be used in studies for other cohort populations with modified dr iving scenarios or experiment designs.
Subject Geospatial Information Systems
Keyword(s) Driving behaviour
eye tracking
multi-GNSS RTK
visual-motor coordination model (VMCM)
DOI - identifier 10.1080/14498596.2016.1149116
Copyright notice © 2016 Mapping Sciences Institute, Australia and Surveying and Spatial Sciences Institute.
ISSN 1449-8596
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