United States Department of Transportation
i
Techniques for mining truck data to improve freight operations and planning.
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2006-05-01
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[PDF-2.37 MB]
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NTL Classification:NTL-FREIGHT-FREIGHT;NTL-FREIGHT-Trucking Industry;NTL-FREIGHT-Freight Planning and Policy;
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Abstract:Freight plays an increasingly valuable role in the national economy, and a growing percentage of
freight – measured by both total volume and market value - is being moved along the highway
system by truck. An important part of the research process to fully understand the impacts of
these increased truck volumes on the entire transportation network is by collecting and analyzing
freight data. With the adoption of just-in-time supply chain management solutions, and
increasing congestion on urban, rural and intercity motorways, better knowledge of freight
movements can serve to improve highway operations. The real-time data generated by the
development of travel time algorithms can be provided to commercial vehicle operators to enable
them to minimize the delay associated with goods movement, and assist in streamlining the
logistics planning process. Increased knowledge of truck travel patterns has the potential to
increase overall highway safety, lead to better-managed maintenance operations, provide cost
savings to public agencies, validate investments in intelligent transportation systems (ITS), and
improve long-range planning and forecasting. Like other aspects of traffic engineering, efforts
that result in higher quality data and improved collection methodologies generally lead to
increased knowledge of the transportation system. This paper explores techniques that use
current ITS technologies such as the Autoscope video processing system and loop detector data
algorithms to collect and verify short and long vehicle count and length data. Three sets of traffic
data for each time interval are created, and then compared using statistical analyses to produce
results that that reveal new information about the freight transportation system in the Portland
metropolitan region.
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