A Modular Colored Stochastic Petri Net for Modeling and Analysis of Signalized Intersections

Abstract

The dynamic behavior of traffic lights regulating a network of intersections can be viewed as a complex discrete-event system that can be modeled and controlled by Petri nets. In this paper, a bilayer signalized control method is presented. In the lower layer, a colored stochastic Petri net controls the signal indication displays and stage transitions. In the upper layer, a supervisory logic layer decides which stage should be serviced next. The proposed model increases modularity, reduces complexity, and, more importantly, is capable of being used to implement various signal control strategies. The method is used to implement four different control strategies: pretimed control, fully actuated control, semiactuated control, and random stage selection (as a benchmark) in the context of a signalized traffic network containing six intersections. Extensibility and future potential research to further enhance the proposed method are discussed and proposed at the end.