A macroscopic signal optimization model for arterials under heavy mixed traffic flows

Yen Yu Chen, Gang Len Chang

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


This paper presents a generalized signal optimization model for arterials experiencing multiclass traffic flows. Instead of using conversion factors for nonpassenger cars, the proposed model applies a macroscopic simulation concept to capture the complex interactions between different types of vehicles from link entry and propagation, to intersection queue formation and discharging. Since both vehicle size and link length are considered in modeling traffic evolution, the resulting signal timings can best prevent the queue spillback due to insufficient bay length and the presence of a high volume of transit or other types of large vehicles. The efficiency of the proposed model has been compared with the benchmark program TRANSYT-7F under both passenger flows only and multiclass traffic scenarios from modest to saturated traffic conditions. Using the measures of effectiveness of the average-delay-per-intersection approach and the total arterial throughput during the control period, our extensive numerical results have demonstrated the superior performance of the proposed model during congested and/or multiclass traffic conditions. The success of the proposed model offers a new signal design method for arterials in congested downtowns or megacities where transit vehicles constitute a major portion of traffic flows.

Original languageEnglish
Article number6675786
Pages (from-to)805-817
Number of pages13
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number2
StatePublished - Apr 2014


  • Arterial control
  • multiclass traffic
  • signal optimization


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