Madrid
- City size
- Large
- European region
- Southern Europe
Madrid
Solutions Tested in Real Life Demonstration
Pilot objective
Test digital and data-driven solutions to improve curbside management, delivery operations, route planning and the management of shared logistics facilities.
Solutions tested in real‑life demonstration
- KER8Dynamic Curbside Management Tool
- KER10IT Pop-Up Delivery Points Management Tool
- KER12Congestion Forecasting & Safe Route Planning (CargoConnect)
- KER13Advanced Management IT Cockpit of Shared Facilities
Dynamic Curbside Management Tool
Dynamic Curbside Management Tool
Pilot Focus
Madrid tested a dynamic curbside management system that uses digital signage, on-street infrastructure and software to manage the allocation of curb space for different uses throughout the day. The pilot focused particularly on supporting urban freight operations, while also testing the technical and operational feasibility of dynamically managed curb space and the collection of occupancy data.
What worked during the demonstration?
- The physical and digital components of the solution — including poles, on-street equipment and software — were successfully developed and deployed.
- The pilot demonstrated the technical feasibility of implementing flexible, dynamic curbside management in a real urban environment.
- Strong support from the district was a key implementation enabler.
- Madrid's mobility ordinance provided sufficient regulatory flexibility to authorise an innovative pilot in public space.
- Close collaboration between the city and the technology developer supported implementation.
What were the challenges and barriers?
- Providing a reliable power supply for the equipment proved challenging — the equipment was deliberately designed to be self-standing, to avoid an intrusive on-street installation, which made powering it harder.
- The pilot could not be made mandatory, limiting the city's ability to ensure the dynamically allocated uses were respected — a limitation of the experimental framework that should be factored into how user behaviour is interpreted.
- Occupancy could be monitored automatically via sensors, but compliance with the dynamically assigned uses was not automatically enforced and depended largely on voluntary user behaviour, which required resource-intensive in-person visual monitoring.
Factors to assess for replication & required adaptations
Governance & pilot authorisation
Madrid's mobility ordinance provided sufficient flexibility to authorise an experimental intervention in public space, though mandatory compliance could not be fully enforced during the pilot.
Establish a regulatory framework allowing temporary pilot authorisations.
Infrastructure readiness
Fabrication of poles, on-street equipment and software design were key implementation steps. Providing electrical power for data collection equipment was challenging.
Ensure adequate electrical infrastructure and installation locations before deployment; consider autonomous power alternatives.
Site selection
The pilot location combined commercial activity, schools, high parking occupancy, low turnover and parking indiscipline.
Select locations where competing curbside demands justify dynamic management, and conduct a baseline assessment before defining time allocations.
Operational programming
Different curbside uses need to be allocated according to demand at different times of day.
Define initial time slots using local demand data and allow them to be adjusted following evaluation.
Institutional cooperation
District support was a strong success factor. Close collaboration between the city, district and technology developer was key to implementation.
Build strong cooperation between municipalities, districts and technology providers.
Operational monitoring capacity
Monitoring and control resources were limited.
Allocate sufficient monitoring and enforcement resources.
Key lessons learned
Main takeaways from implementation
- Collaboration between the city, district and developer is an important enabler.
- Regulatory flexibility enabled the authorisation of the pilot under Madrid's mobility ordinance.
- Early infrastructure planning strongly influences deployment success.
Recommendations
Action-oriented advice for future adopters
- Develop clear regulatory frameworks for innovation pilots.
- Ensure suitable electrical infrastructure before deployment.
- Strengthen cooperation between all implementation partners.
- Allocate sufficient operational resources for monitoring.
- Dynamic curbside management is not primarily a technology challenge; it requires coordination between regulation, infrastructure, local stakeholders and operations.
- Local institutional support is a major implementation enabler — early involvement of the district helped resolve practical deployment issues.
- Regulatory flexibility is essential, but authorisation alone is not sufficient; monitoring and enforcement arrangements should be defined before deployment.
- Infrastructure requirements should be assessed during site selection — power supply and installation constraints can significantly affect implementation.
- Curbside allocation should be demand-driven rather than based on fixed assumptions; baseline data are necessary to determine the appropriate number of spaces and time windows for each use.
- Pilot evaluation should distinguish technical performance from behavioural and mobility impacts.
IT Pop-Up Delivery Points Management Tool
IT Pop-Up Delivery Points Management Tool
Pilot Focus
Madrid demonstrated an IT-supported pop-up delivery management solution designed to allocate temporary delivery locations for logistics operators. The pilot evaluated the use of existing operational data together with digital management tools to support more flexible and efficient last-mile delivery operations while assessing the feasibility of the concept under real logistics conditions.
What worked during the demonstration?
- DHL's historical operational data supported evaluation.
- The existing mobility ordinance enabled testing.
What were the challenges and barriers?
- DHL could not fully test the pilot under real operational conditions because of contractual commitments.
- GDPR and privacy regulations prevented sharing vehicle registration data.
Factors to assess for replication & required adaptations
Operational feasibility with logistics operators
DHL had historical operational data that could support the evaluation. However, the logistics operator could not test the pilot under real delivery conditions due to contractual and operational commitments to customers.
Confirm operators can participate under real operating conditions before defining the pilot.
Governance & pilot authorisation
The mobility ordinance includes an article allowing pilots to be tested on streets. This regulatory flexibility helped enable implementation.
Introduce regulatory provisions allowing temporary logistics pilots.
Data governance & privacy
Due to data protection and privacy regulations, the city department responsible for logistics management could not share vehicle registration data.
Address GDPR constraints before implementation.
Infrastructure synergies
Using the same installation as KER8 made implementation easier. Shared infrastructure helped reduce deployment complexity.
Reuse existing infrastructure where possible to reduce deployment effort.
Key lessons learned
Main takeaways from implementation
- Reusing existing infrastructure (KER8 hardware) reduced deployment effort and implementation time.
- Early engagement with logistics operators is a strong enabler.
- Privacy requirements should be addressed before deployment.
Recommendations
Action-oriented advice for future adopters
- Verify operator participation before launching pilots.
- Reuse existing infrastructure whenever possible.
- Develop GDPR-compliant alternatives for required datasets.
Congestion Forecasting & Safe Route Planning (CargoConnect)
Congestion Forecasting & Safe Route Planning (CargoConnect)
Pilot Focus
Madrid integrated municipal logistics data into the CargoConnect navigation platform to support congestion forecasting and safer route planning for freight vehicles. The pilot incorporated information such as loading and unloading areas, vulnerable zones and other municipal datasets to improve route planning for urban logistics operators.
What worked during the demonstration?
- Municipal logistics data was successfully integrated into the navigation platform.
- Sensitive areas, vulnerable users and loading/unloading locations were incorporated into routing.
- The availability of high-quality municipal logistics datasets enabled more accurate and context-specific route planning.
What were the challenges and barriers?
- The routing software was originally designed for cargo bikes, but DHL — the operator participating in this pilot — does not operate cargo bikes, and most deliveries in Madrid are made by truck. Adapting the tool took extra time and development effort.
- Madrid does not have real-time traffic data, which is important for a route-planning tool.
Factors to assess for replication & required adaptations
Municipal data integration
Municipal data was integrated into the navigation platform, including data on sensitive areas, vulnerable zones, and loading/unloading locations.
Prepare relevant municipal logistics datasets before integrating them into routing tools.
Key lessons learned
Main takeaways from implementation
- The lack of real-time traffic data in Madrid limits the route planner's ability to respond dynamically to traffic conditions. Cities considering replication should assess the availability, quality and accessibility of real-time mobility data early on.
- Understanding operators' requirements, fleet characteristics and available city data before implementation can reduce additional development effort and facilitate smoother deployment.
Recommendations
Action-oriented advice for future adopters
- Prepare structured municipal logistics data before deployment.
- Ensure routing tools can incorporate local restrictions and logistics infrastructure.
Advanced Management IT Cockpit of Shared Facilities
Advanced Management IT Cockpit of Shared Facilities
Pilot Focus
Madrid tested an advanced IT cockpit for managing shared logistics facilities through camera-based monitoring and digital management software. The pilot evaluated the deployment of the monitoring system in a real logistics environment while assessing its ability to support the management and operation of shared logistics facilities.
What worked during the demonstration?
- A suitable pilot location enabled testing in a real logistics environment.
- Camera installation and software deployment could be completed easily and successfully, ahead of operational validation.
- Municipality and public managers could identify fraudulent use of the parking spaces.
- The tool accurately recognised plate numbers across a wide range of situations and vehicle types.
What were the challenges and barriers?
- GDPR and privacy regulations prevented sharing vehicle registration data.
- Lack of proper enforcement due to legal constraints.
Factors to assess for replication & required adaptations
Site suitability & real logistics environment
A suitable pilot site was available, allowing the solution to be tested in a real logistics environment.
Identify representative logistics sites before deployment.
Technical deployment of camera & software
Implementation involved installing the camera and designing the software, built as a self-standing device to avoid an intrusive on-street installation.
Secure a supplier for the camera solution and ensure an electricity connection is available at the site.
Data governance & privacy
Due to data protection and privacy regulations, the logistics department could not share vehicle registration data.
The most straightforward way to manage the solution is via shared vehicle registration data; however, depending on the complexity of the local context, checking the authorised plate number may need to be done differently.
Key lessons learned
Main takeaways from implementation
- Installation is very straightforward — the only requirements are an electricity connection and phone signal coverage.
- GDPR issues need to be resolved in advance to get the most out of this type of solution.
- A proper legal framework is needed to support enforcement.
Recommendations
Action-oriented advice for future adopters
- Select representative logistics sites for testing.
- Assess GDPR implications before selecting camera-based monitoring technologies, and define the mechanisms needed to ensure proper enforcement in the event of misuse of parking spaces.
