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The assessment of strategies designed to manage the continued growth in road-based freight and associated externalities has been hampered by a paucity of disaggregate data on commercial vehicle movements. When disaggregated data are available, the analysis of commercial vehicle route and trip chain structure can provide insightful information about urban commercial vehicle tours, travel patterns, and congestion levels. Over the past 15 years, the ability to collect detailed travel information has been expanded by developments in global positioning system (GPS) technology. In mid-2006, a GPS survey of commercial vehicles was piloted in Melbourne, Australia, to support a major update of freight data and modeling capabilities in the metropolitan region. The survey used passive GPS methods in which the truck driver's involvement in the data collection effort was minimal. The contributions of this research to the field of urban freight data collection were fourfold: (a) describing implementation issues with the data collection, (b) detailing the algorithms used to process the raw GPS data into meaningful travel and trip information, (c) presenting a discussion of pilot survey data tour results, and (d) discussing potential uses and limitations of GPS technology in urban freight modeling and planning. Despite processing challenges, GPS provides an appealing method to enrich commercial vehicle data collection and enhance our understanding of on-road behavior. Because increasing numbers of commercial vehicles become equipped with GPS receivers, only privacy concerns remain as a major barrier to gathering and using such data on a widespread basis in the future.
Greaves et al. (Tue,) studied this question.
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