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SUMMARY

Every year, nearly 1.2 million persons are killed and 50 million are injured in road crashes

around the world. Road crashes are anticipated to be among three top leading causes of
deaths in the world by 2020. In Australia, almost 1,400 people are killed and 32,000 people

are severely injured in road crashes annually. Of the different types of vehicles involved in

crashes, heavy vehicles are a major traffic safety concern, due to their higher likelihood of
involvement with fatal and severe injury accidents.

In Australia, heavy vehicles contribute significantly to the nation's economy because they are

the major means for transporting goods in the country. In addition, it is predicted that heavy
vehicle traffic will increase by 50 per cent by 2030. Therefore, the increase in the number of

heavy vehicles will add to safety concerns because the probability of vehicle crashes

increases by five per cent when the heavy vehicle percentage is higher than 30 per cent of
total traffic volume. On the other hand, although heavy vehicles comprise only a small

percentage, roughly 3% of the total registered vehicles, this type of vehicle is involved in

18% of total road fatalities. Therefore, the reduction in the number of crashes involving
heavy vehicles has been proposed as one of the key performance indicators in the National

Road Safety Strategy 2011-2020 for Australia.

To reduce the trauma of heavy vehicle crashes, more research is needed to provide a better
understanding of the factors influencing the frequency and severity of these crashes. The aim

of this research is to identify the factors influencing heavy vehicle crashes and injury severity

in Victoria, Australia. Therefore, in this research project, three studies were carried out to
provide evidence-based recommendations to enhance the safety of heavy vehicles and save

lives on Australian roads. In the first study, a crash severity model is developed to determine
the variables influencing single-vehicle crashes involving heavy vehicles at intersections and

mid-blocks. In the second study, a crash injury severity model is developed to determine the
neighbourhood socioeconomic variables that influence injury severity in heavy vehicle

collisions. Finally, in the third study, a crash injury severity model is developed to determine

the causes contributing to injury severity in heavy vehicle angle collisions.

In the first study, the objective was to identify the factors differentiating between single
heavy vehicle collisions at intersections and mid-blocks using a binary logit model. The
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