Exploiting New Data Sources to Quantify Arterial Congestion and Performance Measures

Transit travel time, operating speed and reliability all influence service attractiveness, operating cost and system efficiency. These metrics have a long-term impact on system effectiveness through a change in ridership. As part of its bus dispatch system (BDS), the Tri-County Metropolitan Transportation District of Oregon (TriMet) has been archiving automatic vehicle location (AVL) and automatic passenger count (APC) data for all bus trips at the stop level since 1997. In 2014, a new and higher-resolution bus AVL data collection system was fully implemented. This new AVL system provides stop-level data as well as five-second resolution (5-SR) bus position data between stops. Rather than relying on interpolation tools to estimate bus trajectories (including stops and delays) between stops, the higher-resolution data show more precise bus positions along each trip. Bus travel speeds and intersection signal/queuing delays may be determined using this newer information of several variables on transit travel time. This research project explored potential applications of the new data for assessing transit performance, and for estimating transportation system performance measures for urban streets and arterials. Results suggest that the 5-SR data provide high-resolution time and position information which can be used to determine bus travel speeds between stops, identify speed breakdowns, and estimate intersection signal/queuing delays. Additionally, high-resolution achieved bus data can be used to visualize sources of congestion and delay on urban arterials. A new inter-stop trip time model was developed using the five-second resolution data. This newly developed model resulted in statistically significant and improved results over previous models. The models for overall travel time indicated that dwell time and average speed between stops were the major factors influencing transit travel time. Hence, it was concluded that estimation of average speed between stops is a critical component of the transit trip time models. Using this 5-SR data in the trip time model led to more precise and statistically valid trip time models. The research provides conclusions that can be used by transit agencies to improve operations through improvements such as transit signal priority. More importantly, for transit agencies looking for ways to archive data the research provides recommendations on formatting the data that can be most useful for future analysis.

• Record URL:
  http://ppms.trec.pdx.edu/media/project_files/NITC-RR-770_New_Data_Sources_To_Quantify_Arterial_Congestion.pdf
• Summary URL:
  http://nitc.trec.pdx.edu/research/project/770
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/32928
• Supplemental Notes:
  • This research was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Portland State University

  Department of Civil and Environmental Engineering, P.O. Box 751
  Portland, OR  United States  97207-0751

  California Polytechnic State University, San Luis Obispo

  1 Grand Avenue
  San Luis Obispo, CA  United States  93407

  National Institute for Transportation and Communities

  Portland State University
  P.O. Box 751
  Portland, OR  United States  97207

  Research and Innovative Technology Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Figliozzi, Miguel
  • Bertini, Robert L
  • 0000-0001-5580-5293
  • Glick, Travis B
  • 0000-0001-6936-9111
  • Stoll, Nicholas B
  • Feng, Wei
  • Sidhu, Bobjot S
  • Pande, Anurag
  • 0000-0002-3456-7932
• Publication Date: 2017-1

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; Maps; References; Tables;
• Pagination: 47p

Subject/Index Terms

• TRT Terms: Arterial highways; Automatic vehicle location; Average travel speed; Bus transit; Data collection; Dwell time; Mathematical models; Performance measurement; Traffic congestion; Traffic delays; Travel time
• Identifier Terms: Tri-County Metropolitan Transportation District of Oregon
• Uncontrolled Terms: High resolution data
• Subject Areas: Data and Information Technology; Operations and Traffic Management; Public Transportation;

Filing Info

• Accession Number: 01641045
• Record Type: Publication
• Report/Paper Numbers: NITC-RR-770
• Files: UTC, NTL, TRIS, RITA, ATRI, USDOT
• Created Date: Jun 30 2017 8:25AM