Traffic Light Controller for Parallel Railroad Level Crossing Traffic Control Systems Using Deterministic and Stochastic Petri nets

Deterministic and stochastic Petri nets (DSPNs) are well utilized as a visual and mathematical formalism to model discrete event systems. This paper proposes to use them to model parallel railroad level crossing control systems. Their applications to both single and double-track railroad lines are illustrated. The resulting models allow one to identify and thus avoid critical scenarios in such systems by conditions and events of the model that control the phase of traffic light alternations. Their analysis is performed to demonstrate how the models enforce the phase of traffic transitions by a reachability graph method. Their important properties are verified. In this paper, we employ DSPNs to model a parallel railroad level crossing system and identify its critical scenarios for the purpose of their complete avoidance. This helps advance the state-of-the-art in traffic safety related to the intersection of railroads and roadways.