Congestion rates in urbanised areas of Australia have becoming an increasing issue with the rate of population growth. Studies that exist don’t elaborate on what factors influence travel times but more on how to decrease congestion. It is therefore thought that if the exact causes of traffic congestion aren’t properly known, how can it be addressed properly? The purpose of this thesis is to answer the question: What factors influence travel time and traffic congestion? Through the gathering of data, both quantitative and qualitative, and analysis the factors of traffic congestion and their importance can be found.
The data was gathered through the conduction of travel time surveys using the ‘floating car method’ and was gathered for a period of two and a half years. Once enough data and perceived factors were gathered, they were then cleaned, filtered and analysed using multiple linear regression (with dummy variables for qualitative factors.
The outcome of this thesis showed that the perceived predictions of factors, such as leaving after peak times will decrease travel time, were confirmed. However, some anomalies were also found. These anomalies consisted of crashes and rainfall increasing averages speeds.
It is concluded that, although some factors need more survey runs to get a more reliable data set, the reliability of the data will always be questionable as constant improvements to the study area are made with time. It has also shown that because of this, the data output is becoming more predictable.
In conclusion the main factors that increase congestion in the peak periods for AM are starting the survey run between the times of 7:30 – 8:15am and the months of February and March. While decreased congestion is a result of school holidays and the Westfield Chermside Shopping Centre expansion.
The factors that increase congestion in the peak PM periods are starting the survey run between 5:00 – 5:45pm, Thursdays and the month of March. The factors that help in decreasing congestion in the PM runs are rainfall (11-30mm) and the Month of January.
Although this thesis was conducted for the congestion rates along the northern corridor of Brisbane, the general factors that appear in the output can be a good indication of similar situations faced all over the world.