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ZENODO
Audiovisual . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Audiovisual . 2024
License: CC BY
Data sources: Datacite
ZENODO
Audiovisual . 2024
License: CC BY
Data sources: Datacite
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Petri Nets Models for Safety-Critical Systems

Authors: Hense, Andreas;

Petri Nets Models for Safety-Critical Systems

Abstract

How can safety-critical systems be analyzed to ensure that dangerous states cannot occur?This video introduces the modeling and analysis of safety-critical systems using Petri nets, focusing on a railway crossing as a representative example. The video explains how a railway crossing can be modeled as a Petri net and how the corresponding reachability graph can be used to formally verify safety properties. In particular, it is shown that the model guarantees that the crossing gates cannot be open while a train has a green signal to pass the crossing. The example demonstrates how formal modeling and state-space analysis support reasoning about correctness and safety in systems where failures may lead to serious harm. The video illustrates how Petri nets provide a rigorous foundation for the design and validation of safety-critical control systems. Related resource:- WoPeD homepage and download: https://woped.dhbw-karlsruhe.de This is video #49 of the BPASeries.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average