An Adaptive Signal Control Method Using Cell Transmission Model and Mixed Integer Linear Programming

Adaptive signal control is a favorable way to reduce the congestion and improve the mobility of urban traffic networks. This paper proposes an adaptive signal control algorithm to optimize the signal timing for the incoming cycle at an isolated intersection. Traffic volume prediction and signal optimization are two crucial components of adaptive control methods. A CTM-based model predicts the traffic volumes for the target intersection by counting the current vehicle numbers in the upstream cells. This model does not make assumptions about the arrival process and the correlation of the flows between consecutive cycles. Through this method, the accuracy of the volume prediction is ensured even under a rapidly varying traffic conditions. In addition, the signal optimization problem is modeled as a mixed integer linear program (MILP) based on the Barron-Jensen/Frankowska (B-J/F) solution to the Lighthill-Whitham-Richards (LWR) model. The sequence and the splits of phases can be optimized at the same time according to the current traffic condition. Finally, this paper compares the new method to the critical lane flow ratio method which is a commonly used strategy. The total delay per vehicle resulting from the new method is reduced under degrees of traffic congestion ranging from low to high.

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

    Transportation Research Board

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  • Authors:
  • Conference:
  • Date: 2019

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 10p

Subject/Index Terms

Filing Info

  • Accession Number: 01698315
  • Record Type: Publication
  • Report/Paper Numbers: 19-05850
  • Files: TRIS, TRB, ATRI
  • Created Date: Mar 1 2019 3:51PM