Doctoral Degrees (Civil Engineering)

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Browsing Doctoral Degrees (Civil Engineering) by Subject "Automobile drivers -- Attitudes"

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    Towards the extension of the knowledgebase to further the understanding and modelling of driver behaviour
    (Stellenbosch : Stellenbosch University, 2003-04) Poolman, Pieter; Bester, C. J.; Stellenbosch University. Faculty of Engineering. Dept. of Civil Engineering.
    ENGLISH ABSTRACT: The problem of how the mind relates to the brain stands as one of the greatest challenges today. The materialistic worldview and pragmatic approach to social problems are both being transformed by discoveries of how human experience and culture arise in cerebral activity. Even so, this effort, spearheaded by neuroscience, has seen the important and contentious issue of driver behaviour somehow been left behind. From an extensive literature study, it can be concluded that gross disregard of the neural underpinnings of such behaviour tied to a behaviouristic approach is endemic to the field. Numerous qualitative psychological models (each associated with debates about their validity) and Artificial Intelligence models, which effectively only imitate robots 'impaired' to display some humanlike characteristics, were come across. Although neural networks are derived from current knowledge of computation within the brain and deployed in industry, human driver behaviour modelling is not benefiting from this revolution in humanlike information processing. To date, very little has been done to determine what makes road users speed, drive while drunk, overtake, or yield at crossroads. As the central nervous system is the human measuring device in and of the world and thus key affector of human behaviour, it is ofutrnost importance to invest resources in 'inoculating' the field of driver behaviour modelling onto a robust basis provided by neuroscience. Being a human driver incorporates a broad complement of interrelated brain systems to perform driving tasks (psychological functions) at hand, such as lane keeping, speed choice, risk perception, and obstacle avoidance. The proper level of analysis of such a psychological function is the level at which that function is represented in the brain. Providing a theoretical model of human behaviour, based on biological facts of the brain as a whole, is surely a challenge for decades to come, but the field of driver behaviour should be part of such an effort. Collaboration is needed among investigators from the fields of neuroscience, psychology, mathematics, computer science, and engineering to further driver behaviour modelling. It is uncommon that professionals from these fields have a thorough understanding of the other fields involved, but the author, not pretending to be an expert, argues that such a union of fields will be of significant value not only to transportation, but all behavioural sciences. The wealth of to-date knowledge amassed in neuroscience lies ready to be tapped by researchers interested in explaining human driver behaviour. To this end, the use of modem brain-imaging techniques will be invaluable in pinning down the neural correlates of particular driving subtasks, bearing in mind the extent of structural impacts on the brain of each individual, brought about by a lifetime of interaction with the environment. Thus, based on the findings of this literature study, the author proposes that supplementary work be conducted by a multi-disciplinary team to roll-out an experiment to study the nature of environmental stimuli as instigators of aggression and road rage, by drawing on knowledge about brain imaging and (amygdala) activation.