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A driver visual attention model

University of British Columbia

This thesis proposes a driver visual information acquisition model which gathers information based on a selective process so events such as distractions can be modelled. This model contains visual information gathering capabilities and visual attention mechanisms based on subjective and objective factors. As the research focused on applicability, the model's framework was designed to be integrated as a component processor within a microscopic computer traffic simulation. The model determines visual attention using two mechanisms: internal and external focusing. The Internal Focusing Mechanism is a proactive attention director. This subjective-based mechanism directs the driver's attention to a general direction such that information relevant to the current task is actively searched for based on the driver's expectancy. The External Focusing Mechanism is a reactive attention director based on the characteristics of the objects within the driver's visual field. External control allows for distractions to be modelled, since irrelevant information may objectively demand higher attention than information relevant to driving. For each visible object, these two control mechanisms determine its Attention Demand Value (ADV). Visual information from the object with the highest ADV is then acquired. The ADV also plays a role in determining the information processing time, amount of attention allocated to driving, and whether visual information is acquired through the foveal or peripheral vision. With the use of this model and its input of various internal and external variables, it is hoped that a variety of driver types with varying visual abilities (e.g. age-related, intoxicated) can be simulated within visually detailed environments. Key Words: visual attention, information acquisition, attention demand value, driver behavior, perceptual object

Thesis/Dissertation

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2009-03-25

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http://hdl.handle.net/2429/6544

Civil Engineering

University of British Columbia

UBCV

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