SORTEDMOBILITY stands for Self-Organized Rail Traffic for the Evolution of Decentralized MOBILITY. It proposes a holistic approach for self-organizing management of public transport operations in urban and interurban areas, specifically focusing on rail transport as a mobility backbone.

In this approach, intelligent trains will operate in a self-organized manner to guarantee high levels of service in the multi-modal public transport context. The rail transport system will be more resilient, capable of self-adapting to an evolving environment with respect to the demand and in case of disruptions.

Furthermore, it will strive for multi-modal integration with other public transport modes enhancing multi-actor cooperation and market competitiveness.

A simulation assessment will allow the comparison of the self-organization approach with the traditional centralized one. It will integrate novel advanced methods for passenger demand prediction and rail traffic modeling, including new operational concepts such as train platooning.

Suitable KPIs will be introduced and measured in different case studies, in Denmark, Italy and France. They will illustrate how the new approach improves the public transport system and effectively reduces disturbance peaks and propagation. In a close collaboration between academic and key rail stakeholders, SORTEDMOBILITY will showcase the future of railways while producing a set of guidelines and recommendations to support the design and implementation of future public transport systems. 

SORTEDMOBILITY is organized in seven work packages (WPs).

WP1 “Operational Principles and KPIs for Self-Organizing Railway Operations” constitutes the foundation for the rest of the project. Here, the principles shaping the concept of self-organizing rail traffic management are defined, concerning both the decentralized decision making process and the relevant rail operational principles. Moreover, it will define the KPIs that will be used for assessing the SORTEDMOBILITY holistic approach.

Based on these operational principles and aiming to the improvement of these KPIs, passenger demand is carefully studied in WP2 “Mobility Demand Modeling” and a distributed algorithm for rail traffic management is designed and implemented in WP3 “Algorithms for Self-Organizing Railway Operations”. These two work packages will strongly rely on AI techniques and they will build on the existing state of the art in the fields of machine learning, swarm intelligence and transport optimization, railway in particular.

A state-of-the-art microscopic simulation platform, EGTRAIN, will be enhanced in WP4 “Simulation Platform for the Assessment of Self- Organizing Railway Operations”. It will also be integrated to the outputs of WP2 and WP3 to allow the thorough assessment of the proposed self-organizing approach in a realistic laboratory environment.

Such assessment will be carried out in WP5 “Case Studies and Impact Assessment”. This work package will first supply data and scenarios of different case studies for the development of the various research streams. Second, it will carry out the actual assessment of the SORTEDMOBILTY holistic approach, and, third, it will elaborate guidelines and recommendations based on this assessment. They will be aimed to support the railway industry in the potential migration to the self-organized traffic management operations envisaged in the project.

The work organization is finalized throughWP6 “Dissemination and Exploitation” and WP7 “Project Management”.