Insights Gained by Incorporating Continuous Vehicle Length Data into Empirical Freeway Bottleneck Diagnosis

There are many essential measured fundamental traffic data parameters including vehicle count, occupancy, and speed that can be used for transportation planning, design, operations, and performance monitoring/management in real time and over longer periods of time. Federal, state, regional/local agencies, and the private sector invest substantial resources toward collecting traffic data. Fundamental traffic data can also help to identify bottleneck locations, provide information to travelers, track economic impacts of travel demand, reveal traffic pattern changes due to incidents and construction, and can be converted to key performance measures. A small portion of this overarching data collection effort includes vehicle classification stations that provide truck counts (and lengths) for freight planning, pavement design, operations and enforcement purposes. There is a distinctive data stream available for the freeway system in the Portland, Oregon region, supported by the PORTAL data hub. In addition to housing continuous 20-sec vehicle count, speed, and occupancy data for more than 1,000 sensors since 2004, this system uniquely provides volume bins at 4 length-based classifications. This study analyzes traffic conditions along an 18-mile section of southbound I-5 in Portland. In order to reveal bottleneck locations and their activation times, oblique curves of cumulative vehicle count, time-mean speed, truck volume, and total vehicle length were utilized. Both bottleneck locations and their activation times were found to be reproducible from day to day. The availability of a continuous stream of vehicle length data revealed unique, high resolution, spatiotemporal features of freeway traffic hitherto unavailable to the researcher or practitioner.


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 19p

Subject/Index Terms

Filing Info

  • Accession Number: 01763966
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-03885
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:16AM