Identification Of Railway Transport Systems Using Stochastic P-Timed Petri Nets Model

The Railway transportation networks can be considered as discrete event systems with time constraints. The time factor is a critical parameter, since it includes dates and schedules to be respected in order to avoid overlaps, delays and collisions between trains. Petri nets have been recognized as powerful modelling and analysis tools for discrete event systems with time constraints. So, they are suitable for railway transportation systems. This article is devoted to the modelling and identification of the Tunisian Railway Network. The proposed approach consists in identifying, from experimental measurements, the dynamical behavior of the system by using interpreted Stochastic P-timed Petri Nets (SP-TPNs). The resulting model is suitable to simulate the traffic and also to evaluate the influence of different types of disturbances on the expected schedule.