Development of a Delay Model for Unsignalized Intersections Applicable to Traffic Assignment

The purpose of this research is to develop a model for estimating unsignalized intersection delay which can be applicable to traffic assignment (TA) models. The current unsignalized intersection delay models have mostly been developed for operational purpose, and demand detailed geometric data and complicated procedures to estimate delay. These difficulties result in the unsignalized intersections delay being ignored or assumed as a constant in TA models. A video camera and vehicle license plate number recognition method were used respectively to collect traffic volume and measure delay during peak and off-peak traffic periods at four unsignalized intersections in the city of Tehran, Iran. Data on geometric design elements were measured through field survey. An empirical approach was used to develop a delay model as a function of influencing factors based on the 5- and 15-min time intervals. The proposed model estimates the delay of each approach based on the total traffic volume and Right of Way of the subject approach and the intersection friction factor. The effect of conflicting traffic flows was implicitly considered by using the intersection friction factor. As a result, the developed delay model is separable that guarantees the convergence of TA solution methods. A comparison between delay models produced using different time intervals showed that, increases from 43.2 (%) to 63.1 (%) as time interval increases from 5- to 15-min. The HCM delay model was validated using the field data, and it was found that it overestimates the delay, especially at high delay range.


  • English

Media Info

  • Media Type: DVD
  • Features: Figures; References; Tables;
  • Pagination: 2p
  • Monograph Title: TRB 89th Annual Meeting Compendium of Papers DVD

Subject/Index Terms

Filing Info

  • Accession Number: 01157840
  • Record Type: Publication
  • Report/Paper Numbers: 10-2224
  • Files: TRIS, TRB
  • Created Date: Jan 25 2010 11:01AM