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Journal Article

Citation

Sun QC, Xia JC, He J, Foster J, Falkmer T, Lee H. Accid. Anal. Prev. 2018; 113: 85-96.

Affiliation

School of Occupational Therapy and Social Work, Curtin University, Australia. Electronic address: h.lee@curtin.edu.au.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.aap.2018.01.019

PMID

29407672

Abstract

Visual information for a driver is predominant during driving. Linking drivers' visual search patterns with motor behaviour helps understand how drivers perceived spatial and hazardous information to regulate their physical movements. Visual-motor coordination performance can be a sensitive indicator for driver competency assessment. Due to age-related cognitive decline, older drivers are likely inefficient in visual-motor coordination. While poor visual-motor coordination can cause risky behaviour behind the wheel, it is yet challenging to examine it owing to the complexity of driving behaviour. By reviewing how vision guides driving, we proposed a gaze-based integrated driving assessment approach. The empirical data were from 38 older drivers aged 60 to 81 years, who completed an on-road driving assessment recorded by eye tracking and vehicle movement tracking. Their visual search attributes were extracted from eye tracking video frames and linked to vehicle positions. Driving data, drivers' cognitive condition and driving section were encapsulated into an integrated database, allowing interrogating multi-faceted driver-vehicle-environment interactions. Exploratory analysis results show that older drivers' performed different visual search patterns at roundabout and intersection manoeuvres. Older drivers with better executive function skills performed more frequent eye fixations on the curves and inside vehicle features. The investigation of visual-motor coordination performance demonstrated the feasibility and effectiveness of using the integrated approach in assessing older drivers' performance.

Copyright © 2018 Elsevier Ltd. All rights reserved.


Language: en

Keywords

GIS; Gaze-based integrated driving assessment; Older drivers; Visual pattern; Visual-motor coordination

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