Optimization of coordinated-actuated traffic signal system: Stochastic optimization method based on shuffled frog-leaping algorithm

Study has shown that about half of the traffic signalized intersections in the United States need to be reoptimized. Even though many traffic signal control systems have been upgraded from pretimed controllers to actuated and adaptive controllers, traffic signal optimization software has not kept up with such advances. For example, existing commercial traffic signal timing optimization programs such as SYNCHRO and TRANSYT-7F do not optimize advanced controller settings (e.g., minimum green time, extension time, detector settings) available in modern traffic controllers. This deficiency is due partly to existing programs, which are based on macroscopic simulation tools that do not explicitly consider individual vehicular movements. To overcome such a shortcoming, a stochastic optimization method (SOM) was proposed and successfully applied to a few case studies. This study presents some enhancements made in the SOM and case study results from an arterial network consisting of 16 signalized intersections. The proposed method employs a distributed computing environment for faster computation time and uses a shuffled frog-leaping algorithm (SFLA) for better optimization. The case study results showed that the proposed enhanced SOM method, called SFLASOM, improved total network travel times over field settings by 3.5% for midday times and 2.1% for p.m.-peak times. In addition, corridor travel times for both p.m.-peak and midday times were significantly improved.