Resilient Mixed Integer Linear Programming Formulation for Heterogeneous Traffic Signal Priority Scheduling Problem

Traffic signal priority (TSP) is a common operation at signalized intersections to accommodate the green requests from special vehicles like buses or ambulance as well as emerging connected automated vehicles (CAV). The special vehicles requiring the TSP service can be classified into two categories: high-priority special vehicles such as fire trucks, ambulances or trains and low-priority special vehicles like buses or trams, etc. The high-priority TSP requests are hardly deniable because the incurred delay otherwise may result in loss of lives or fatal crashes whereas the low-priority TSP requests can be declined or postponed if certain conditions cannot be met. While most TSP strategies today allow for placing the TSP requests only 20 to 30 seconds away, special vehicles or CAVs can transmit TSP requests via mobile computing technique minutes before they arrive at the downstream intersections. This new feature offers additional flexibilities in the TSP scheduling problem. In this paper, the authors present a resilient optimization framework for heterogeneous TSP scheduling based on a recently developed phase-time network model. The heterogeneous priorities of TSP requests is interpreted as various lengths of TSP time windows in the phase-time network. As a result, scheduling heterogeneous TSP requests over time is viewed as a vehicle routing problem with pickup time windows (VRPTW). Unlike most ad-hoc green-extension or red-truncation-based TSP strategies, this new method will not break the existing traffic signal control configuration and therefore will minimize the negative impact on the mobility of background traffic. Two mathematical programming formulations are developed: (i) Mixed Integer Linear Programming (MILP) formulation and resilient MILP formulation (R-MILP). The R-MILP formulation is modified from the basic phase-time work model in such a way that the mathematical solver can always reach a mathematically feasible solution but the solution is not necessarily feasible in the real world. This features enable the authors to identify those infeasible conditions for the TSP scheduling. Four numerical experiments are conducted to validate and examine the robustness of the proposed approach.

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

    Transportation Research Board

  • Authors:
    • Chowdhury, Farzana
    • Wang, Peirong (Slade)
    • Li, Pengfei (Taylor)
    • Zhang, Li
    • Yang, Xianfeng (Terry)
    • ORCID 0000-0002-9416-6882
  • Conference:
  • Date: 2019


  • English

Media Info

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

Subject/Index Terms

Filing Info

  • Accession Number: 01698317
  • Record Type: Publication
  • Report/Paper Numbers: 19-06026
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:52AM