Compositional modeling of railway Virtual Coupling with Stochastic Activity Networks

The current travel demand in railways requires the adoption of novel approaches and technologies in order to increase network capacity. Virtual Coupling is considered one of the most innovative solutions to increase railway capacity by drastically reducing train headway. The aim of this paper is to provide an approach to investigate the potential of Virtual Coupling in railways by composing stochastic activity networks model templates. The paper starts describing the Virtual Coupling paradigm with a focus on standard European railway traffic controllers. Based on stochastic activity network model templates, we provide an approach to perform quantitative evaluation of capacity increase in reference Virtual Coupling scenarios. The approach can be used to estimate system capacity over a modelled track portion, accounting for the scheduled service as well as possible failures. Due to its modularity, the approach can be extended towards the inclusion of safety model components. The contribution of this paper is a preliminary result of the PERFORMINGRAIL (PERformance-based Formal modelling and Optimal tRaffic Management for movING-block RAILway signalling) project funded by the European Shift2Rail Joint Undertaking.

Safe-Platoon

Building a safety model to make expert decisions is an approach to improve the safety of a system. The issue of safe modeling and analyzing such domain is still an open research field. Providing quantitative estimation of a system's safety is an interesting method to study system complexity. This article explores the author's current methods and proposes a new formal model for quantitative estimation based on a stochastic activity network (SAN). This model is built based on some failure modes that affect platoon vehicles.