Microscopic Datasets: A Novel Approach Applied to Visualization of Spatiotemporal Flow Regions

A parsimonious approach to microscopic traffic flow datasets is suggested. This approach is based on provision of minimal data, along with a set of supporting tools termed as feature extraction operators that are intended to provide researchers with the flexibility to extract those particular features of the data that they desire to study. As an illustration of the possibilities of this approach, an attempt is made to validate the hypothesis that traffic flow decomposes into spatiotemporal regions representing one of the four classes of congested flow, shock wave, acceleration wave or free flow. This approach employs the classical conceptual framework of the field of pattern recognition, as applied to microscopic datasets. The specific microscopic dataset employed is that labeled “I-405 Northbound at Mulholland Drive, Los Angeles” in the 1985 study conducted by JHK Associates for the Federal Highway Administration (FHWA). The classical approach of plotting and manually analyzing vehicle trajectories is initially employed, to establish some approximation to ground truth. Then it is demonstrated that speed alone is inadequate to support the desired classification. Finally, a 4-means cluster analysis in velocity-acceleration feature space is employed to demonstrate that a spatiotemporal plot of the resulting cluster numbers provides a decomposition more-or-less as expected.

• Record URL:
  • http://swutc.tamu.edu/publications/technicalreports/167452-1.pdf
• 
• Supplemental Notes:
  • This research was funded by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Texas Transportation Institute

  Texas A&M University System, 3135 TAMU
  College Station, TX  United States  77843-3135

  Southwest Region University Transportation Center

  Texas A&M University
  3135 TAMU
  College Station, TX  United States  77843-3135
• Authors:
  • Nelson, Paul
  • Fields, Matthew J
• Publication Date: 2006-5

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: 33p

Subject/Index Terms

• TRT Terms: Cluster analysis; Flow visualization; Mechanical acceleration; Microscopic traffic flow; Pattern recognition systems; Traffic flow; Vehicle trajectories; Velocity
• Identifier Terms: U.S. Federal Highway Administration
• Uncontrolled Terms: Congested flow; Free flow (Traffic); Shock waves (Traffic); Spatiotemporal data; Traffic patterns
• Geographic Terms: Los Angeles (California)
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01031648
• Record Type: Publication
• Report/Paper Numbers: SWUTC/06/167452-1, Report 167452-1
• Contract Numbers: 10727
• Files: UTC, TRIS
• Created Date: Aug 24 2006 4:28PM