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Title: The influence of mood and cognitive load on driver performance : using multiple measures to assess safety
Author: Zimasa, Tatjana
ISNI:       0000 0004 7431 8142
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2018
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Emotions and moods are an inevitable part of human life. Previous research suggests that positive and negative moods affect human performance in many aspects: decision making, perception, reasoning and memory. The influence of mood on drivers’ behaviour has been studied to a less extent and mainly with respect to negative emotions. The studies reported in this thesis are based on psychological theories regarding the differences in the effects of positive and negative moods on information processing and mind wandering. The thesis describes two studies: a desktop study and a driving simulator study, which measure drivers’ responses to the actions of other traffic, their observational patterns and driving behaviours in a variety of scenarios. The effects of neutral, happy, sad and angry moods were studied. The simulator study also investigated possible ways to disconnect drivers’ minds from mood induced mind wandering by using different types of cognitive load. The results suggest that mood valence and arousal have different effects on driving safety, with negative moods resulting in the most dangerous driving. In order to draw conclusions about the effect of mood, a combination of multiple measures (e.g. glance patterns, driving performance and drivers’ physiological measures) should be analysed. The results also suggest that some amount of cognitive load, applied while driving, can have a positive effect on drivers’ attention. Further research is needed to establish the amount and type of the cognitive load necessary to improve drivers’ ability to maintain their attention on the driving task. Studies with a larger number of participants and field studies are needed to validate the findings. It is suggested that the findings are used to improve in-car assistance systems able to both detect the harmful effects of a driver’s emotional state and re-direct their attention to the primary task of driving.
Supervisor: Jamson, Samantha ; Henson, Brian Sponsor: EPSRC ; JLR
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available