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1.6 Thesis Outline

The remainder of this thesis is organised as follows:

Chapter 2 briefly introduces the models that have been applied to predict crash severity in the
research literature and identifies the advantages and disadvantages of each crash severity

model type. In addition, this chapter presents a summary of previous studies on the

differences in the characteristics of crashes occurring at intersections and mid-blocks, and the
influence of neighbourhood socioeconomic characteristics on crashes. Finally, the major

limitations of the existing heavy vehicle crash studies are identified and presented.

Chapter 3 report on the first study to identify the factors differentiating between single heavy-
vehicle crashes at intersections and mid-blocks in the Melbourne metropolitan area. This

chapter is based on a research paper published in the Journal of Advanced Transportation

(Balakrishnan, S., Moridpour, S., and Tay, R. 2016).

Chapter 4 reports on the second study to identify the factors contributing to road-user injury
severity in crashes involving heavy vehicles. In addition to identifying the factors

contributing to heavy-vehicle crash severity, this study also provides some evidence-based

recommendations to improve the safety of heavy vehicles.

Chapter 5 reports the results of the third study to identify the factors contributing to
occupants’ injury severity in crashes involving at least one heavy vehicle. Specifically, two-

vehicle collisions in angle crashes in the state of Victoria are analysed using four logistic

regression models. The chapter compares the binary logistic, skewed logistic, and mixed logit
(with uniform and normal distributions for the random parameters) models to check the

robustness of the results and compares their relative performances when applied to data that
are moderately skewed.

Chapter 6 summarises the major results of this research and discusses future research

directions.

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