Stochastic Performance Analysis of the Contraflow Left-Turn Lane Design Considering the Influence of Upstream Intersection

The present paper conducted a stochastic analysis of the operational performance of the contraflow left-turn lane (CLL) design considering the influence of the upstream signalized intersection. The arrival distribution was generated using the platoon dispersion model. A stationary condition in which the number of discharged left-turning vehicles in both the contraflow lane and the conventional lane would be constant in any stationary cycles was defined. The authors proved that the CLL system will always reach the stationary condition after a few cycles if the arrival distribution is fixed. In stationary cycles, the CLL design consistently generates either recurrent and constant residual queues or no queues, depending on the arrival distributions of left-turning vehicles. Considering the stationary condition, analytical models were developed for estimating the capacity and delay for left-turns at signalized intersections with the CLL design. The results showed that both the arrival pattern and the length of the contraflow lane could significantly influence the operational performance of the CLL design. The residual queues in the stationary condition might significantly increase control delay, indicating that left-turning vehicles could experience longer delay if the contraflow lane is not properly designed. An optimization method was then proposed for minimizing the control delay by optimizing the length of contraflow lanes and the offset between intersections considering fixed left-turn demand. The research results can be directly used by traffic engineers to optimize the CLL design, and to estimate the operational performance of the signalized intersections with the CLL design.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AHB25 Standing Committee on Traffic Signal Systems.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
    • Wu, Jiaming
    • Liu, Pan
    • Zhou, Yang
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Photos; References; Tables;
  • Pagination: 6p

Subject/Index Terms

Filing Info

  • Accession Number: 01698318
  • Record Type: Publication
  • Report/Paper Numbers: 19-05246
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:52AM