Comparative performance analysis of multi-objective transit-priority systems

Yaser E. Hawas, Md Didarul Alam

Research output: Contribution to journalConference articlepeer-review


This paper demonstrates how can the Response Surface Methodology (RSM) simulation-based optimization be used in calibrating the transit priority based advanced traffic control systems. Three types of control types are considered; split, protected, dual phasing signal control. The proposed methodology is applied to some integrated heuristic based control that accounts for various triggers such as downstream signal congestion and identification of priority transit vehicle in traffic streams. The RSM accounts for multiple objectives related to the various network measures of effectiveness simultaneously by estimating the so-called composite desirability. Multiple objective functions were used; namely, maximizing the transit throughput and minimizing the mean travel time simultaneously. The three control types were analyzed under various network loading levels reflecting congested and highly congested scenarios. The RSM methodology proved to be efficient in optimizing the various control types, increasing the transit throughput and decreasing the mean travel time in almost all studied cases. Comparative analysis was conducted to assess the effectiveness of the various controllers in terms of transit throughput and mean travel time. A simplified multi-criteria ranking indicated the best performance in the case of dual, followed by the split, and finally the protected control.

Original languageEnglish
JournalWorld Congress on Civil, Structural, and Environmental Engineering
Publication statusPublished - 2018
Event3rd World Congress on Civil, Structural, and Environmental Engineering, CSEE 2018 - Budapest, Hungary
Duration: Apr 8 2018Apr 10 2018


  • Calibration
  • Multi-objective functions
  • Response surface methodology
  • Traffic control
  • Transit signal priority

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Environmental Engineering


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