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Assessing the spatial impacts of multi-combination vehicles on an urban motorwayLennie, Sandra Christine January 2005 (has links)
Multi-combination vehicles (MCVs) in urban areas impact on productivity, safety, infrastructure, congestion and the environment. However, psychological effects of MCVs on other drivers may also influence the positioning of vehicles and congestion. A literature review revealed little information on the psychological effects of heavy vehicles on other road users. This research can be used to quantify some psychological impacts of MCVs.
A testing program was undertaken on the Gateway Motorway to observe passenger car behaviour around MCVs in a lateral and longitudinal sense. Video footage was collected on a four lane divided urban motorway section which was level, straight and away from any off/on ramps. It experiences high traffic volumes with a one-way AADT of approximately 33,500. The route is currently designated for B-doubles, which is the most common MCV in urban areas.
In a lateral sense, the research showed that passenger car behaviour changes around heavy vehicles (prime mover semi-trailer combination and B-doubles); however, there is no statistical difference in passenger car behaviour around semi-trailers and B-doubles. Longitudinally it was found that, even though passenger cars shy away from B-doubles more than semi-trailers, B-doubles are still more efficient in a spatial sense since they carry more freight.
The outcomes of this research indicate that there is no further psychological impact on passenger cars, when travelling around B-doubles compared with semi-trailers. Where the results identified longitudinal behaviour changes, it was still concluded that B-doubles were more efficient at transporting freight when the passenger car equivalent (PCE) per tonne of freight was considered.
Tracking ability testing was undertaken in a rural area to determine the lateral spatial requirements of three different MCVs. The rural testing was considered appropriate since parts of the urban network have similar characteristics to rural networks. A model was developed as a part of this project to process the data collected by Haldane (2002), but results could not be relied upon due to poor quality data.
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