Quantifying periodic railway network capacity using petri nets and macroscopic fundamental diagram

Szymula, Christopher; Bešinović, Nikola; Nachtigall, Karl

doi:10.1016/j.trc.2023.104436

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…"I" stands for the input function from P (places) to T (transition). "O" denotes the output function from T to P. "M 0 " represents the initial markings, which is the initial distribution of tokens in places when the system starts [8,9].…”

Section: Petri Nets and Their Types And Applicationsmentioning

confidence: 99%

Dynamic Simulation and Modeling of a Novel NeuRaiSya for Railway Monitoring System Using Petri Nets

Deplomo,

Villaverde,

Paglinawan

2024

Sensors

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This research introduces the NeuRaiSya (Neural Railway System Application), an innovative railway signaling system integrating deep learning for passenger analysis. The objectives of this research are to simulate the NeuRaiSya and evaluate its effectiveness using the GreatSPN tool (graphical editor for Petri nets). GreatSPN facilitates evaluations of system behavior, ensuring safety and efficiency. Five models were designed and simulated using the Petri nets model, including the Dynamics of Train Departure model, Train Operations with Passenger Counting model, Timestamp Data Collection model, Train Speed and Location model, and Train Related-Issues model. Through simulations and modeling using Petri nets, the study demonstrates the feasibility of the proposed NeuRaiSya system. The results highlight its potential in enhancing railway operations, ensuring passenger safety, and maintaining service quality amidst the evolving railway landscape in the Philippines.

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Section: Petri Nets and Their Types And Applicationsmentioning

confidence: 99%