This report presents a stochastic traffic signal optimization method that consists of a heuristic simulation model and the microscopic simulation model CORSIM. For the heuristic optimization method, three heuristic methods including a genetic algorithm (GA), simulated annealing (SA) and OptQuest Engine were investigated and finally the GA was selected. The main feature of the GA-based stochastic signal control settings optimization method is the ability to optimize not only Group 1 settings (i.e., cycle length, green splits, offsets, and phase sequences) but also Group 2 (i.e., controller and detector-related settings) and Group 3 settings (i.e., volume-density control related settings) in the microscopic simulation environment represented by CORSIM. The performance of the proposed stochastic optimization method was compared with existing signal timing optimization programs including TRANSTY-7F and SYNCHRO under a microscopic simulation environment. The results indicate that the proposed method outperformed existing programs in the optimization of the basic four parameters, and also showed that additional controller and detector-related settings can further improve the operations of coordinated actuated signal control systems. (Author/publisher)
Samenvatting