Title:
Applying item response theory to measure drivers' perceived complexity of roadway environments
Applying item response theory to measure drivers' perceived complexity of roadway environments
Author(s)
Shaw, Faaiqa Atiyya
Advisor(s)
Roberts, James S.
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Abstract
Roadway environments constitute visually complex systems within which users make split-second critical decisions on a daily basis. As such, understanding transportation system user perceptions and performance across varied roadway environments is crucial for a broad array of transportation research and engineering purposes (e.g. understanding safety data trends, informing roadway design guidelines, etc.). This thesis applies item response theory (IRT) to identify and interpret the dimensions present that influence drivers’ perceived complexity of roadway environments. We find that a four dimensional polytomous Graded Response Model best measures this data, and were able to ascertain that participants’ perceived complexity ratings were most affected by their perception of freeway and urban environments, as well the visibility and traffic conditions of the particular roadway. This study enables not only an understanding of the factors that influence driver perception of the built environment, but demonstrates an application of multidimensional, polytomous IRT to study transportation system user perceptions; one of the first known implementations of multidimensional IRT within transportation engineering.
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Date Issued
2018-08-17
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Thesis