Increasing demand for road freight has lead to a widespread adoption of more-productive large freight vehicles (LFVs), such as B-Doubles, by Australia's road freight industry. Individual LFVs have a greater potential to impact traffic efficiency through their greater length and poorer longitudinal performance. However, this is offset to an extent as fewer vehicles are required to perform a given freight task on a tonne-km basis. This research has developed a means of characterising the effects that large freight vehicles have on the performance of an urban arterial corridor managed by signalised intersections. A corridor-level microsimulation model was developed from first principles, which modelled the longitudinal performance of individual vehicles to a greater accuracy than most existing traffic simulation software does. The model was calibrated from traffic counts and GPS-equipped chase car surveys conducted on an urban arterial corridor in Brisbane's southern suburbs. The model was applied to various freight policy and traffic management scenarios, including freight vehicle mode choice, lane utilisation and traffic signal settings; as well as the effectiveness of green time extension for approaching heavy vehicles. Benefits were able to be quantified in terms of reduced travel times and stop rates for both heavy and light vehicles in urban arterial corridors.

An origin-destination (O-D) matrix of truck travel was obtained from the City of Hamilton. The concept of Passenger Car Equivalence (PCE) was used to transform this matrix into a passenger car O-D matrix. The integrated land-use and transport model IMULATE has been modified to incorporate the transformed vehicle matrix, along with a matrix for passenger cars. A PCE value of zero implies the total absence of trucks in the network. Reported emission values in this case are attributed to passenger cars alone. PCE values greater than zero indicate the number of vehicles displaced in traffic flow by the presence of a single truck. Reported emissions under such conditions are affected by the presence of trucks. The results suggest that the estimation procedure is effective. The contribution of trucks to mobile emissions of HC, CO, NOx, and PM has been addressed at the aggregate and link levels. Emission estimates demonstrate sensitivity to the presence of trucks as modeled in this study. The presence of trucks is shown to increase the aggregate level of all pollutants and affect changes in link-based estimates. While the results are encouraging it has been recognized that the potential of this procedure for generating accurate estimates is limited by the resolution of the observed truck data. It is also recognized that gas PM is emitted at such low rates that it is difficult to measure accurately. Another limitation of the present study is that only trips with origins and destinations within the Hamilton CMA are included. The contribution of trucks passing through the CMA is not dealt with, but warrants future consideration. Also, the reported results refer only to the morning peak period. The contribution of truck emissions during the rest of a typical day is expected to be significant since most freight trips avoid the morning peak period. / Thesis / Master of Arts (MA)