Techniques for mining truck data to improve freight operations and planning.

Details

• Creators:
  Bertini, Robert L. ; Horowitz, Zachary ; Tufte, Kristin ; Matthews, Spicer
• Corporate Creators:
  Portland State University. Department of Civil & Environmental Engineering
• Corporate Contributors:
  Transportation Northwest Regional Center X (TransNow) (UTC) ; Oregon. Department of Transportation
• Subject/TRT Terms:
  Freight Service Intermodal Services Transportation Operations Trucking
• Publication/ Report Number:
  TNW2006-05
• Resource Type:
  Research Paper
• Geographical Coverage:
  United States
• Corporate Publisher:
  Oregon. Dept. of Transportation
• 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.
  
  
• Format:
  PDF
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:48a5e769446c395be0d8a6635a28a57e82b5b49d74c220830e4ff2d2c6480abbdf729bb70a8e5272e66e4a425f05c656e15c0946482a67e3b5f82c4c0c1f1059
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/5538/dot_5538_DS1.pdf
• File Type:
  [PDF - 2.37 MB ]