Year: 2016
Type: dissertation
Abstract: Driving is a complex visuomotor task, and the study of eye movements can provide interesting \nand detailed insights into driving behaviour. The aim of this thesis was to understand (a) what \nmethods are useful to assess driving behaviour, (b) the reasons we observe differences in eye \nmovements when driving, and (c) offer a possible visual training method. The first experiment \ncompared drivers’ eye movements and hazard perception performance in an active simulated \ndriving task and a passive video driving task. A number of differences were found, including \nan extended horizontal and vertical visual search and faster response to the hazards in the video \ntask. It was concluded that when measuring driving behaviour in an active task, vision, \nattention and action interact in a complex manner that is reflected in a specific pattern of eye \nmovements that is different to when driving behaviour is measured using typical video \nparadigms. The second experiment investigated how cognitive functioning may influence eye \nmovement behaviour when driving. It was found that those with better cognitive functioning \nexhibited more efficient eye movement behaviour than those with poorer cognitive functioning. \nThe third experiment compared the eye movement and driving behaviour of an older adult \npopulation and a younger adult population. There were no differences in the eye movement \nbehaviour. However, the older adults drove significantly slower, suggesting attentional \ncompensation. The final experiment investigated the efficacy of using eye movement videos \nas a visual training tool for novice drivers. It was found that novice drivers improved their \nvisual search strategy when driving after viewing videos of an expert driver’s eye movements. \nThe results of this thesis helps to provide insights into how the visual system is used for a \ncomplex behaviour such as driving. It also furthers the understanding of what may contribute \nto, and what may prevent, road accidents.
Author: Andrew Mackenzie
Language: English
Topic: Traffic and Road Safety
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2943116835