A Practical Approach to Managing Intersection Traffic Data for Large Scale Studies
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A Practical Approach to Managing Intersection Traffic Data for Large Scale Studies

Filetype[PDF-61.13 KB]


  • English

  • Details:

    • Corporate Creators:
    • Resource Type:
    • TRIS Online Accession Number:
      00793272
    • ISBN:
      0965231046
    • Edition:
      2000-5-15 to 2000-5-16
    • Corporate Publisher:
    • Abstract:
      As an increasing number of metropolitan areas study the possibility of enhancing the modal options of their transportation systems, the number of Environmental Impact Statements (EIS) that need to be prepared has increased significantly. A recent EIS for Tampa, Florida was conducted that required peak hour intersection Level of Service (LOS) calculations for over 60 intersections for two base-year and seven future-year scenarios (nearly 1,100 intersection data records). Tight time constraints and the need for efficient stewardship of this large data set lent itself to employing a data management tool. The proper tool would encompass electronic data management as well as provide signal optimization and LOS calculations. The traffic engineering software package Synchro was chosen for this task. Existing turning movement counts (TMC), geometric conditions, and signal timing were entered into peak period Synchro files. The Synchro base year TMC were exported in comma delimited (CSV) file format and converted to approach turn percentages using a spreadsheet program. The regional transportation planning model output provided daily link volumes for each scenario. Intersection approach volumes were then determined using historical K and D factors. Incorporating the approach volumes into the TMC spreadsheet provided horizon year TMC. The TMC were then imported back into the Synchro file and optimized to provide future year intersection LOS. This innovative procedure saved considerable time in both data error checking and traffic analysis. Once the data set was entered into Synchro, all further data management and analysis was electronically handled, therefore reducing data entry time and the potential for data handling errors.
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