Smart mobility
A city is more than the sum of its intersections
A minor disruption at one intersection can propagate across a whole corridor, affecting travel times, public transport, pedestrians and emissions. Optimising each traffic light on its own is not the same as optimising mobility across a city.
01The challenge
Local decisions. City-wide consequences.
Vehicle flows, pedestrian demand, public transport, incidents, weather and temporary restrictions interact in ways fixed schedules cannot capture. A timing change at one junction can shift queues elsewhere.
Effective mobility intelligence needs adaptation, coordination and a clear understanding of how each operational recommendation was generated.
02What ETR brings
Adaptive decisions with an inspectable trail
Adaptive responses
Learn from changing traffic patterns instead of relying only on fixed control strategies.
Cross-variable intelligence
Evaluate interactions between flows, congestion, pedestrian demand and operational priorities.
Traceable recommendations
The conditions and logic behind each proposed adaptation stay inspectable.
Distributed intelligence
A foundation for progressively coordinating decisions across connected intersections.
Safety constraints and traffic-engineering oversight remain essential throughout development and validation.
03In simulation
Watch ETR coordinate a real traffic ring
A recorded SUMO simulation of ten real traffic lights in Ingolstadt, Germany: the same morning demand run with the city’s real signal programs and with ETR. Follow how each light, junction, corridor and the city level reads its own scope, decides and explains why.
Illustrative simulation on a public benchmark scenario, not the Barcelona pilot and not pilot results.
04The pilot
MOB-IA: from digital twin to the streets of Barcelona
- Partner
- ACISA
- Programme
- Barcelona Innova Lab · Mobility Challenge
- Status
- Selected Nov 2026 · pilot planned for late 2027
- Scope
- Traffic prediction, coordinated signals, digital twin
ACISA’s MOB-IA proposal was selected in November 2026 as one of the winning solutions of the Barcelona Innova Lab Mobility Challenge. The Mindkind contributes its adaptive, explainable AI to the collaboration.
The pilot, planned for the end of 2027 and not yet operational, will explore traffic prediction and coordinated signal management using a digital twin of the road network. Evaluation can address corridor travel time, queue propagation, flow stability and the transparency of recommendations.
05Evolution path
What ETR does today, and what comes next
The same architecture grows level by level. Later levels are planned capabilities of ETR, not results already shown in this application.
- WORM
- FLY Today
- BEE Next
- MOUSE Future
- PRIMATE
- HUMAN AGI target
FLY Available today
Learn non-linear relationships between traffic conditions and operational outcomes.
BEE Next capability
Evaluate action–consequence relationships in controlled simulations and digital twins.
MOUSE Future capability
Context-aware planning and coordination across multiple intersections and time horizons.
06ETR in action
More applications
The Mindkind
AGI is the destination.
Traceable adaptive intelligence is the business on the way.
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