Barcelona
• Data sets of 3 focus areas
• 6 multimodal and traffic service innovations
• 2 new innovations in sustainable mobility management
Barcelona will be implementing two sets of iterative use cases that will pilot deployEMDS data space infrastructure to advance the regional mobility strategy.
Multi-operator data governance ecosystem for bus fleets and demand-responsive transport
Cluster: Public transport operation
This use case aims to enhance the Multi-Fleet Operation and Information System (SAEi) system, a next-generation multi-fleet management and passenger information system for regional public transportation.
This includes:
- Integrating dynamic bus transport: Improving the integration of bus services for better planning and optimisation for the benefit of operators and passengers.
- Developing governance and standardisation: Enhancing quality monitoring and standardising data governance across different bus modes, aligning with regional digitalisation goals.
- Incorporating third-party services: Enabling data usage control for third-party services, adding value through insights like anonymised mobile data.
- Preparing for European integration: Aligning with European data standards to ensure cross-border compatibility and market access.
This approach supports the integration of diverse data and services, improving transportation planning and passenger experience while reducing costs.
Background:
The Metropolitan Transport Authority (ATM) coordinates Barcelona’s public transportation, encompassing a consortium of regional and local administrations, to enhance the digitalisation and operational efficiency of public transit through the SAEi system. A key challenge is integrating diverse data sources and ensuring interoperability across multiple operators to provide comprehensive and real-time information to passengers.
Forecasting system to optimise traffic based on vehicle flow and air quality
Cluster: Data for mobility planning
The objective of this use case is to enhance usage of sensor data, both in the city of Barcelona and along the ring road. The analysis will lead to improved traffic management and higher transportation efficiency.
This includes:
- Developing Artificial Intelligence/Machine Learning models: Creating models for traffic prediction, incident detection, and air quality impact assessment.
- Supporting standardisation and governance: Establishing governance mechanisms to ensure data integrity and proper usage across regions and sectors.
- Integrating with EMDS: Facilitating broader data-sharing initiatives across Spain’s private and public sectors.
This initiative aims will make the most of data products to ultimately inform mobility policy makers, empowering urban planning across European cities.
Background:
The current traffic information system in Barcelona lacks integration with related datasets and relies on manual processes for data interoperability. Historical data exists but lacks direct correlation between variables or predictive capabilities. Expertise is crucial for interpreting traffic impacts due to the system’s fragmentation and lack of contextual integration, hindering objective impact assessment, such as traffic’s effect on air quality or weather’s influence on traffic.
