FEDORA has published Deliverable D5.2 – Modular Simulation Platform and Sim2Real Techniques, bringing together new tools designed to make the project’s simulation environment more flexible, reusable and better able to support the transition from virtual experiments to real-world applications.

A central achievement is a modular simulation platform that acts as a common orchestration layer between different simulation environments and the logic modules developed within FEDORA, including control, optimisation and behavioural models. Instead of building separate integrations for each module and simulator, the platform enables them to communicate through a shared interface, making it easier to connect the same logic to different simulation environments or, in the future, real pilot sites. A demonstrator for traffic signal control illustrates this approach, showing how different control strategies can be tested within the same framework and evaluated through a common pipeline.

The deliverable also explores Sim2Real techniques—methods for transferring solutions developed in one simulation environment to another, and ultimately towards real-world applications. In a proof-of-concept experiment, an AI-based traffic control strategy was trained in one simulator and tested in another. The results showed that simply transferring the trained strategy is not enough: using the proposed Grounded Action Transformation method, developed and evaluated within FEDORA improved performance in almost all of the tested configurations.

A third strand of work focuses on foresight and scenario testing. The new platform can create reproducible scenarios combining traffic demand, traveller behaviour, network conditions, control policies and even emerging services such as UAV-based passenger transport. This allows different mobility scenarios to be compared and evaluated using common performance indicators. The approach is currently being tested in the Aglantzia network in Cyprus.

Together, the three components demonstrate how FEDORA’s Simulation Space can bring different models, technologies and experiments together through common interfaces. The work provides an important step towards a flexible simulation environment where new mobility solutions can be tested, compared and refined before moving closer to real-world deployment.

FEDORA has published Deliverable D3.1 – Integrated Cross-Sectoral Data Space, setting out the foundations for a shared environment where organisations can discover, exchange and make better use of mobility data—without giving up control over their own data.

Rather than putting all information into one central database, the FEDORA Data Space connects different organisations and data sources through a federated approach. This means that data can remain with its original provider while still being securely accessed and combined when needed. The approach supports data discovery, exchange and interoperability across different transport modes and sectors.

But simply sharing data is not enough if different systems cannot understand or work with it. The deliverable therefore proposes common data formats, interfaces and metadata standards to improve interoperability. The FEDORA Data Space creates the foundation for a more connected mobility data ecosystem—one where information can move between organisations while respecting data sovereignty, security and common governance principles.

A key element is the FEDORA Public Catalogue, which brings together metadata from a wide range of mobility data sources. This makes it easier for users to discover what data is available and understand how it can be used. The catalogue also provides the foundation for the AI-powered search capabilities, allowing users to find relevant datasets using more natural, accessible queries.

The Mobility Data Harmonisation, Enrichment and Synthetisation Engine (MDHESE) is dedicated architectural module that can be integrated flexibly into data handling workflows to improve and standardise datasets so that information from different sources can be combined more effectively.

D3.1 establishes the architectural and methodological basis for FEDORA’s Data Space, while further developments—including AI-enhanced search and blockchain-based smart contracting—are presented in D3.2 – AI-Enhanced Data Utilization and Smart Contracting. The work will continue to evolve towards the project’s final Data Space implementation.

FEDORA has published Deliverable D4.1 – Optimization and Incentivization Models for Multimodal Networks, presenting a set of new approaches to help cities manage transport networks more efficiently while encouraging people to make smarter and more sustainable travel choices.

The deliverable brings together three key areas of innovation. The first is a Social Optimum Model for multimodal nodes and corridors, designed to look beyond individual journeys and consider how the transport network as a whole can perform better. By using current and historical traffic information, the model can support more balanced management of roads and transport connections, helping reduce congestion and make better use of available network capacity.

The second area explores dynamic pricing and incentives as tools for managing transport demand. Rather than relying only on traditional congestion charges, FEDORA is investigating approaches that could be more acceptable and equitable for travellers. These include non-monetary mechanisms such as tradable mobility credits and “Karma” schemes, as well as ways of communicating incentives more clearly and allocating transport resources according to individual needs.

The third component focuses on optimising multimodal hubs—the places where different transport services come together. The FEDORA tool uses mobility and traffic data to explore where hubs should be located, which services they should provide and how much capacity they need. This work is complemented by a multimodal journey planner and innovative traffic-sensing approaches using UAVs, helping to understand how different solutions could affect traffic and travel behaviour.

Together, these models provide FEDORA with a toolkit for making transport networks more efficient, responsive and user-centred. The approaches will continue to be developed and tested through simulations and real-world pilots, helping identify practical ways to improve mobility while addressing the challenges of congestion, fairness and changing travel needs.

FEDORA has published Deliverable D2.2 – Living Labs Setup, Spaces Definition and Evaluation Models, establishing an important foundation for how the project will develop and test new approaches to multimodal transport management together with the people and organisations who use and operate transport systems every day.

At the heart of the deliverable is FEDORA’s Living Lab approach. During the first year of the project, stakeholders across all six pilot cities took part in workshops to identify local challenges, needs and priorities. These discussions brought together a broad range of perspectives and helped the project understand what different cities need from new mobility solutions—including operational requirements, data availability and governance considerations.

The co-creation process also helped identify and initially validate use cases for each pilot site. By connecting these local challenges with FEDORA’s planned innovations, the project can ensure that the technologies being developed respond to real-world problems rather than being designed in isolation.

A second part of the deliverable defines the FEDORA spaces and evaluation framework. These provide a common structure for bringing together the project’s different technologies and for assessing how well they perform. The work also identifies links and dependencies between the six pilots, helping partners coordinate their activities as the project moves towards its demonstration phase.

Importantly, the Living Lab process is not simply about testing finished technologies. It creates an ongoing dialogue between researchers, transport operators, public authorities and other stakeholders, allowing solutions to be refined as practical challenges emerge.

With D2.2, FEDORA has therefore established the methodological and operational basis for its second year—ensuring that the project’s innovations remain grounded in the needs and realities of the cities where they will ultimately be demonstrated.

FEDORA has published Deliverable D4.2 – Advanced Routing and Mitigation Strategies, introducing a new set of tools designed to help transport networks detect disruptions earlier, optimise routing in real time, and respond more effectively when incidents occur.

The deliverable brings together three complementary components that strengthen multimodal network management across road, public transport and freight systems.

The first is a Complex Event Processing Engine (CEPE), which analyses traffic data in real time to identify unusual events and emerging disruptions. It combines AI-generated synthetic traffic data, short-term traffic forecasting, and computer vision techniques that simulate drone observations. Together, these capabilities help detect incidents and traffic anomalies as they develop, creating an early warning system for network operators.

A second component focuses on multimodal freight routing. The Synchromodal Conflict-Free Vehicle Routing Optimiser helps logistics operators adapt delivery routes when disruptions such as congestion, port delays or other incidents affect the network. By considering different transport modes, vehicle types and real-time traffic conditions, it supports more resilient and efficient freight movements, including last-mile deliveries.

The third innovation is the Dynamic Response Planner, a decision-support tool that helps traffic managers choose the best mitigation strategy once a disruption has been detected. Using traffic simulations, it evaluates different response options—such as adjusting speed limits or managing lane availability—and identifies the combination of measures that can restore network performance most effectively.

Together, these tools create a coordinated workflow: detecting incidents, adapting passenger and freight routes, and recommending targeted response actions. While the current deliverable presents the first proof-of-concept implementations, the next stage of FEDORA will integrate these components with real-world pilot data from cities including Vienna and Nicosia, helping demonstrate how intelligent network management can improve the resilience of Europe’s future multimodal transport systems.

FEDORA has published Deliverable D5.1 – Integrated Multimodal Simulation and Prediction Framework, marking an important milestone in the development of the project’s Simulation Space: a virtual environment where new mobility services, transport policies and network management strategies can be tested before being deployed in real cities.

The Simulation Space brings together three essential building blocks: a city-scale traffic simulation engine, realistic models of traveller behaviour, and controllers that simulate how mobility services and policies operate across a transport network.

One of the deliverable’s main achievements is a new multimodal traffic simulator developed in Python. Rather than modelling every individual vehicle, it captures traffic dynamics at network level while representing cars, buses and trucks. Tested against a detailed simulation of central Athens during the morning peak, it reproduced key traffic patterns with high accuracy while running around 1,000 times faster than the microscopic reference model. This speed makes it ideal for exploring multiple scenarios and supporting future AI-assisted traffic management.

The framework also introduces an agent-based demand model for the Greater Copenhagen Area. Using the open-source SimMobility platform, it creates realistic daily travel schedules for a synthetic population of around 165,000 travellers, representing more than one million trips across a wide range of transport modes, including shared and demand-responsive mobility services.

A third component is a suite of service and policy controllers that models the operation of buses, trains, mobility-on-demand fleets and MaaS platforms, while also enabling the testing of measures such as dynamic pricing and travel credit schemes.

Together, these components establish the technological foundation for FEDORA’s integrated Simulation Space. As development continues, this environment will help project partners evaluate innovative multimodal mobility solutions in a safe, flexible and highly efficient virtual setting—supporting better-informed decisions for the transport systems of tomorrow.