Metro lines are traditionally operated through a combination of planned levels of demand and of availability of rolling stock and drivers along different periods of typical days. The adaptation of operations to face changes of the traffic patterns and levels are largely influenced by the constraints of staff management and by the knowledge of customers expectations.

Additionally, AI and data science are frequently praised as a solution to address transport issues by handling large set of data, combining information from many sources being indicators and sensors.

The Project stemming from this topic should aim to identify and initially exploit key areas of innovation of the future metro system. The initiative shall identify new requirements, develop new concepts, and implement early stages of development of the solutions based on new emerging technologies (automation and digitalization, AI, telecom, etc.).

These new technologies, concepts and new ways of operation shall contribute to a better mass rapid transport system with:

• Optimized Capacity – Flexi Demand, making the most of the existing infra and rolling stock following customer commuting habits, flows and better managing disruptions.
• Efficient Train Control Systems that enable cost reductions and better operational response.
• Sustainable transport system, applying different technologies and concepts to better manage the total cost of ownership and deliver better energy footprint.

The final objective is to increase efficiency, sustainability, attractiveness, and resilience against current state of the art. Making the system future metro systems answering the needs of an evolving society with the metro as the backbone of urban mobility.

Considering the current state of the art regarding automation in the metro system, the action to be funded under this topic shall deliver R&I which first step is to determine requirements and needs for future different type of metro users, while also taking into consideration the resilience to external challenges/future threats (climate threats, sanitary, terrorism, etc.) aiming at making metro systems future proof.

The following R&I areas have been identified as key enablers of the expected outcome. The Project stemming from this topic shall address all the following work streams and is expected to provide all the following:

Workstream 1: Increased adaptability of metros to fluctuations in demand. The project shall deliver a feasibility study, potentially using simulation tools as Proof of Concept to demonstrate to what extent it is possible to increase the adaptability of metros to fluctuations in demand; and how to benefit from new opportunities provided by the trend towards full automation of metro operation (Grade of Operation 4 with no staff on board train), by a better knowledge of customers profiles and travel conditions (expected and actual) thanks to digitalization, by new technologies and by improved coordination with other modes and new mobility services.

Workstream 2: Future of train control. The project shall deliver a feasibility study, including an analysis of the different trends in train control and existing / future technological solutions as well as adefinition of future needs and functional requirements for the different categories of metro systems. The objective is not to focus on one solution with respect to another, but to explore equidistantly the topic from the different point of view like economic, operational, technologic and considering the potential impact on existing systems.

Workstream 3: Advantages and trends brought by AI and data science in metro operation for different types of metros (old/new, large/small, etc.). While their area of relevance is rather associated with large networks, the project shall deliver concepts on the most promising AI and data science implementation applications in metro operation, with a cost-effective approach, in different categories of metro systems (greenfield/brownfield, city or regional, connection with long distance modes...). Relevant aspects like application to operational processes and cybersecurity threat identification and management should also be considered. Preliminary results of this workstream may be considered for Workstream 1 and 2 implementations.

Interactions with other EU-RAIL projects and EU-Missions

The action to be funded under this topic shall:

• Take into account the outputs of linked projects from EU-RAIL Flagship Areas 1^[1], 2^[2] and 3^[3] and work together with them for any potential interfaces.
• Interact with EU-Rail System Pillar^[4] for the aspects related to the interface between mainline rail (SERA) and urban mobility systems of which metro is part.
• Explore possible collaboration with cities participating in the EU Mission for Climate-Neutral and Smart Cities^[5].

Gender dimension

In this topic the integration of the gender dimension (sex and gender analysis) in research and innovation content is not a mandatory requirement.

[1] https://projects.rail-research.europa.eu/eurail-fp1/

[2] https://projects.rail-research.europa.eu/eurail-fp2/

[3] https://projects.rail-research.europa.eu/eurail-fp3/

[4] https://rail-research.europa.eu/system_pillar/

[5] https://ec.europa.eu/mission-cities and Cities Mission Platform https://netzerocities.eu