A Data-Driven Approach for Estimation of Passenger Car Equivalents on Basic Freeway Segments Operating at Capacity

Freeway capacity analyses are critical for transportation professionals to both assess the current state of a facility’s operations and plan for construction. Such analyses involve converting the demand volume into a demand flow rate in units of passenger car per lane per hour through an adjustment that uses a passenger car equivalent (PCE) factor. This PCE factor represents the equivalent effect heavy vehicles have on capacity in terms of a representative passenger car. Estimation of PCEs for basic freeway segments has been a topic of research for decades. Existing studies have often sought to estimate PCEs based on either small sets of data that are not readily available (e.g., individual vehicle headway measurements) or use of traffic microsimulation. Indeed, PCE values used in the 2016 Highway Capacity Manual (HCM) are based on the results of VISSIM simulation. While these approaches have their benefits (for example one can control and adjust many environmental and vehicular factors in a simulation to a very precise degree), they are not without their limitations. Further, such studies have often found results that do not directly agree with those in the HCM or other studies. In order to overcome some of the drawbacks of existing studies, a data-driven approach to estimate PCEs for basic freeway segments operating at capacity is developed herein. The method makes use of large quantities of readily available real-world data, namely, volume and other information obtained from dual loop detectors, in order to estimate PCEs via an equal impedance method.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AHB40 Standing Committee on Highway Capacity and Quality of Service.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
    • Ash, John E
    • Henrickson, Kristian
    • Wang, Yinhai
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: References; Tables;
  • Pagination: 5p

Subject/Index Terms

Filing Info

  • Accession Number: 01698183
  • Record Type: Publication
  • Report/Paper Numbers: 19-04350
  • Files: TRIS, TRB, ATRI
  • Created Date: Mar 1 2019 3:51PM