AI Urban Traffic Flow Optimization
This AI solution uses AI, IoT, and advanced modeling to predict congestion, coordinate traffic lights, and dynamically manage multimodal urban mobility. By orchestrating vehicle, pedestrian, and public transit flows in real time, it reduces travel time, fuel consumption, and emissions while increasing road throughput and reliability for cities and transport operators.
The Problem
“Your signals run on yesterday’s plans while congestion changes every minute”
Organizations face these key challenges:
Signal timing plans are static and require costly, slow retiming cycles—performance degrades weeks after deployment due to demand shifts, construction, or events
Operators watch many feeds but can’t correlate causes across the network fast enough; interventions are reactive and inconsistent by shift/team
Local optimizations (one intersection/corridor) create downstream bottlenecks; transit priority and pedestrian phases are handled with blunt rules
Incidents and surges (stadiums, weather) trigger congestion cascades; ETA reliability and on-time transit performance become unpredictable