DACUS · Project

Software That Manages Drone Traffic So Cities Don't Become Chaos Zones

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Imagine hundreds of delivery drones, air taxis, and inspection drones all flying over a city at the same time — with no human air traffic controller watching them. Someone needs to figure out how many drones can safely fly in a given area, plan their routes so they don't crash, and adjust everything in real time when weather changes or new drones show up. DACUS built the software algorithms and services that do exactly that — a traffic management system for the sky below 150 meters, where drones operate.

By the numbers

consortium partners from aviation and drone industries

European countries represented in the consortium

55%

industry partners in the consortium

total project deliverables produced

prototype services developed and simulation-tested

The business problem

What needed solving

As drone delivery, inspection, and air taxi services prepare to launch across European cities, there is no proven system to manage how many drones can safely operate in a given airspace at the same time. Without demand-and-capacity balancing, urban drone operations face gridlock, safety risks, and regulatory rejection — the same way road traffic without traffic lights leads to accidents and congestion.

The solution

What was built

DACUS built 5 prototype services tested in fast-time simulations: strategic and tactical conflict resolution algorithms, a drone trajectory management system, collision risk models based on real CNS performance, an AI-powered demand prediction model that accounts for weather, and a machine learning-driven dynamic capacity management architecture — totaling 15 deliverables across the project.

Audience

Who needs this

Drone delivery operators scaling to urban fleet operations (e.g., Wing, Amazon Prime Air equivalents in Europe)U-space service providers building traffic management platformsAir navigation service providers (ANSPs) extending services to very low level airspaceUrban air mobility companies developing air taxi servicesCity authorities and regulators planning drone corridors and airspace rules

Business applications

Who can put this to work

Drone delivery and logistics

any

Target: Drone delivery operators and logistics companies planning urban drone fleets

If you are a drone delivery operator planning to scale urban operations — this project developed prototype services for strategic and tactical de-confliction that can handle large numbers of simultaneous drone operations. The AI demand prediction model forecasts real drone traffic demand including weather impacts, letting you plan efficient routes in capacity-constrained airspace. With 11 partners across 6 countries validating the approach, this is built for the European regulatory environment you'll operate in.

Urban air mobility

enterprise

Target: Air taxi and urban air mobility companies

If you are an air taxi company preparing for commercial operations in European cities — this project built drone trajectory management prototypes and dynamic separation algorithms that balance safety with capacity in very low level airspace. The collision risk models factor in real CNS performance, traffic density, and population density on the ground. These tools help you demonstrate to regulators that your operations can scale safely.

U-space service provision

mid-size

Target: UTM/U-space technology providers and ANSPs

If you are a U-space service provider building your technology stack — this project delivered a complete demand and capacity balancing architecture with 15 deliverables covering everything from airspace structure rules to machine learning-based capacity management. The 5 prototype services were tested in fast-time simulations, giving you validated algorithms for conflict resolution, mission planning, and dynamic capacity management that you can integrate into your platform.

Frequently asked

Quick answers

What would it cost to license or use this technology?

The project was a SESAR Research and Innovation Action, and specific licensing terms are not publicly available. Contact the coordinator (CRIDA in Spain) to discuss licensing arrangements for the prototype services and algorithms. As a SESAR project, some outputs may feed into broader European ATM standardization.

Can these algorithms handle real-world drone traffic volumes?

The prototypes were designed to support large numbers of simultaneous operations and were validated in fast-time simulations. The AI demand prediction model and dynamic capacity management algorithms use machine learning to scale decisions. However, live operational deployment at full urban scale would require further validation beyond the simulation testing completed in this project.

Who owns the intellectual property?

IP is shared among the 11-partner consortium led by CRIDA (Spain). The consortium includes 6 industry partners (55% industry ratio) across 6 countries. Licensing discussions should start with the coordinator, though SESAR project IP rules under the EU grant agreement apply.

How does this fit with current European drone regulations?

DACUS was built specifically within the SESAR U-space regulatory context, addressing European Commission priorities for drone traffic management. The airspace structure definitions and separation management processes were designed to align with evolving U-space service requirements (U1-U4). This gives the technology a direct path to regulatory acceptance in the EU.

What was actually delivered and tested?

The project produced 15 deliverables including 5 prototype services: strategic and tactical de-confliction services, drone trajectory management, collision risk models, a dynamic capacity management architecture with machine learning algorithms, and an AI demand prediction model. All prototypes went through at least two development cycles with fast-time simulation testing.

Can this integrate with existing drone management systems?

The architecture was designed as service-oriented, meaning individual components (conflict resolution, demand prediction, capacity management) can be integrated as modular services. The project defined interfaces between DCB process components and existing U-space services, though integration effort will depend on your specific platform.

Consortium

Who built it

The DACUS consortium of 11 partners across 6 countries (Belgium, Germany, Spain, France, Iceland, UK) is led by CRIDA, Spain's ATM research center. With 55% industry participation (6 out of 11 partners) and only 1 SME, this is a consortium weighted toward established aviation industry players and research organizations — exactly the kind of partners needed for technology that must meet strict aviation safety standards. The mix of 2 research institutes and 1 university provides the scientific foundation, while the industry majority signals that practical deployment was a priority from the start.

CENTRO DE REFERENCIA INVESTIGACION DESARROLLO E INNOVACION ATM, A.I.E.Coordinator · ES
INGENIERIA Y ECONOMIA DEL TRANSPORTE SME MP SAparticipant · ES
ENAIREparticipant · ES
EUROCONTROL - EUROPEAN ORGANISATION FOR THE SAFETY OF AIR NAVIGATIONparticipant · BE
JEPPESEN GMBHparticipant · DE
BOEING AEROSPACE SPAINparticipant · ES
TOULOUSE METROPOLEparticipant · FR
TECHNISCHE UNIVERSITAT DARMSTADTparticipant · DE
SOPRA STERIA GROUPparticipant · FR
ISA SOFTWARE LTDparticipant · UK

How to reach the team

CRIDA (Centro de Referencia Investigacion Desarrollo e Innovacion ATM) in Spain — the main ATM research center for ENAIRE, the Spanish air navigation service provider

Order a report on this consortium See CENTRO DE REFERENCIA INVESTIGACION DESARROLLO E INNOVACION ATM, A.I.E. profile →

Next steps

Talk to the team behind this work.

Want an introduction to the DACUS team to discuss licensing their drone traffic management algorithms? SciTransfer can arrange a direct meeting with the right technical contact.

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