The use of cell phone network data in traffic data collection and long-haul truckshed (geographic extent) tracking.

Details

• Creators:
  Wang, Ming-Heng ; Schrock, Steven D. ; Vander Broek, Nate ; Mulinazzi, Thomas
• Corporate Creators:
  Mid America Transportation Center
• Corporate Contributors:
  United States. Dept. of Transportation. Research and Innovative Technology Administration
• Subject/TRT Terms:
  Algorithms Case Studies Cellular Telephones Data Collection Freight Traffic Geographic Information Systems Haul Distance Traffic Data
• Publication/ Report Number:
  MATC-KU: 361 ; 25-1121-0001-361
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Corporate Publisher:
  Mid-America Transportation Center
• NTL Classification:
  NTL-FREIGHT-FREIGHT ; NTL-GEOGRAPHIC INFORMATION SYSTEMS-GEOGRAPHIC INFORMATION SYSTEMS ; NTL-OPERATIONS AND TRAFFIC CONTROLS-OPERATIONS AND TRAFFIC CONTROLS
• Abstract:
  This study analyzed the potential of cell phone positioning techniques in freight truck data collection and long-haul
  
  truckshed (geographic extent) tracking. Freight truck identification and tracking algorithms were developed by means of
  
  cell phone network data and the established freight truck analysis GIS, to recognize freight trucks and determine their
  
  geographic extent (trucksheds). A case study was conducted to illustrate the truckshed tracking process and verify the
  
  tracking results from the cell phone network. Cell phones leaving from the test logistics distribution center were tracked
  
  and classified based on the developed tracking algorithms. The case study also demonstrated the processes of determining
  
  the geographic extent and traffic impact on the transportation network from the test logistics distribution center. The
  
  results showed that the proposed tracking algorithms can identify a similar percentage of freight truck data from the test
  
  facility compared with manual counts. The analysis of geographic extent indicated that 60 percent of freight traffic stayed
  
  within 30 miles of the facility, and approximately 20 percent of the traffic was considered long-haul freight traffic
  
  traveling more than 80 miles away. The long-haul tracking results found that most of the long-haul trucks returned to the
  
  original test facility during the same day. It is recommended that the tracking algorithms and data analysis process could
  
  also be applied to any other freight trucking terminal or intermodal transportation facility, as long as the cell phone
  
  network data are available. A complete freight GIS analysis network around the study area is also recommended to
  
  understand the likely destinations.
  
  
• Format:
  PDF
• Collection(s):
  University Transportation Centers US Transportation Collection
• Main Document Checksum:
  urn:sha256:7b4c8f14b1f2b3459c1a92aaec2f9e4103ab220264e201dc5456f6ce9303b219
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/23125/dot_23125_DS1.pdf
• File Type:
  [PDF - 1.26 MB ]