SEJul 15, 2014

Experience using Coloured Petri Nets to Model Railway Interlocking Tables

arXiv:1407.3891v17 citations
Originality Incremental advance
AI Analysis

This addresses the problem of improving safety and efficiency in railway signaling systems for engineers and operators, but it is incremental as it builds on existing CPN methods with specific enhancements.

The paper tackles the labor-intensive and error-prone process of designing and verifying railway interlocking tables by modeling them with Coloured Petri Nets (CPNs) to assist verification and detect errors rapidly, incorporating features like automatic route setting and cancelling to reduce deadlocks and using CPN Tools features to manage state space size.

Interlocking tables are the functional specification defining the routes on which the passage of the train is allowed. Associated with the route, the states and actions of all related signalling equipment are also specified. It is well-known that designing and verifying the interlocking tables are labour intensive, tedious and prone to errors. To assist the verification process and detect errors rapidly, we formally model and analyse the interlocking tables using Coloured Petri Nets (CPNs). Although a large interlocking table can be easily modelled, analysing the model is rather difficult due to the state explosion problem and undesired safe deadlocks. The safe deadlocks are when no train collides but the train traffic cannot proceed any further. For ease of analysis we incorporate automatic route setting and automatic route cancelling functions into the model. These help reducing the number of the deadlocks. We also exploit the new features of CPN Tools; prioritized transitions; inhibitor arcs; and reset arcs. These help reducing the size of the state spaces. We also include a fail safe specification called flank protection into the interlocking model.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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