A stochastic modeling approach for traffic analysis of a tramway system with virtual tags and local positioning

Abstract

Traditional solutions for tramway interlocking systems are based on physical sensors (balizes) distributed along the infrastructure which detect passing of the trams and trigger different actions, like the communications with the ground infrastructure and the interlocking system. This approach is not easily scalable and maintainable, and it is costly. The SISTER project designed new architectural solutions for addressing the previous problems based on the virtualization of the sensors and on the local positioning of each tram. The key idea is to trigger actions when the computed local position corresponds to a virtual tag. However, the computed position can be affected by errors, compared to the real one. Therefore, it is important to understand the impact of these new solutions on the traffic that can be supported by the tramway network. This paper presents a stochastic modeling approach for analysing the performability of a tramway system based on the SISTER architectural solutions, aiming to identify the parts of the tramway network that are more critical and sensible to the variation of the traffic conditions and to the setting of the key architectural parameters. We build a model using Stochastic Activity Networks and run sensitivity analyses on (i) the accuracy of the positioning, (ii) the different SISTER parameters, and (iii) considering possible outages temporarily blocking the journey of a tram. This analysis allows to properly set and fine-tune the key architectural parameters, to understand the impact of the accuracy on the positioning, to understand the impact of the outages.