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Explore ventureA hierarchical distributed control system that redefines urban traffic as a single, controllable 'City OS' to minimize congestion and accidents.
Explore ventureA private AI that remembers your story, considers compatibility from both sides, and makes room for a real connection.
Explore ventureOrchestrate the city as one organism.
A hierarchical distributed control system that redefines urban traffic as a single, controllable 'City OS' to minimize congestion and accidents.
When everyone takes the same shortcut, that road becomes a bottleneck. TrafficOS coordinates routes, intersections and vehicles across three layers.
Distribute demand across available roads to reduce bottlenecks.
Choose a route for each vehicle using its destination and current congestion.
Align crossing order and speed at intersections and merges.
Same road, same lane closure, same demand.
MEASURED LIVE FROM THIS MODEL · ILLUSTRATIVE, NOT FIELD DATA
Sense, compute, act: over 1,000 cycles a second.
12ms
Edge-to-vehicle latency
Vehicles
Broadcast position, speed and intent.
Edge nodes
Roadside units aggregate data in under 12 ms.
City OS
Computes the best state for the whole city.
Routing
Sends each vehicle its own route.
Execution
Vehicles move as one swarm.
2.4B
Data points per second
<12ms
Edge latency
1K/s
Compute cycles
99.99%
Sync rate
01
Emergency response
Priority corridor creation
Signals turn green in sequence and traffic clears a lane for the ambulance.
−40%
Response time
<8s
Corridor clear
02
Mass events
Stadium & concert egress
Routes are planned hours ahead, so 50,000 people leave across every road.
−65%
Egress time
12×
Routes used
03
Weather adaptation
Dynamic safety margins
Following distances grow and routes avoid flood-prone areas.
−80%
Wet accidents
<30s
Adaptation
04
Work zones
Construction & maintenance
Cars zipper-merge well before the closure, with no stop-and-go.
+90%
Merge efficiency
−75%
Queue length
01
Static signal timing
Timers tuned for yesterday’s average see one intersection, never the grid.
TrafficOS’s approach
The City OS retimes signals and lanes across the grid in real time.
02
“Shortest path” routing
GPS gives every driver the same fastest route, so the route jams.
TrafficOS’s approach
Social routing gives each vehicle a different optimal path.
03
No vehicle coordination
Cars react alone, so one slowdown becomes a miles-long jam.
TrafficOS’s approach
Vehicles talk directly and brake together like a flock.
| Capability | Traditional | TrafficOS |
|---|---|---|
| Optimizes | One vehicle | Whole network |
| Decides | After congestion | Before congestion |
| Communication | None | V2V + V2I |
| Routes | Same for all | One per vehicle |
| Signals | Fixed timers | Adaptive |
| Incidents | Manual | Auto reroute <10 s |
| At scale | Degrades | Improves |
| Data | Past averages | Live + predictive |
Replans every 0.5 s. Forecasts 8 s ahead.
// Simplified flow of the live simulationfunction updateCity(dt) {scanEveryIntersection();if (routeTimer >= 0.5) {replanToSameDestinations({congestion, plannedRoutes, turnDelay});routeTimer = 0;}forecastCrossings({ horizon: 8 });matchSpeedsToCrossingTimes();reserveClearExitsBeforeEntry();sequenceConflictingTurns();openGapsForWorkZoneMerges();accelerateIfClear({ maxKmh: 100 });enforceGapsTurnsAndWorkZones();stepVehicles(dt); // 120 steps / secondcountDestinationArrivals({ seconds: 60 });routeTimer += dt;}
8s
Maximum prediction horizon
0.5s
Route reassessment interval
−60%
Projected congestion reduction across the urban grid
−95%
Safety improvement from coordinated swarm braking
PROJECTIONS · NOT MEASURED RESULTS
01
Digital twin
City-scale simulation.
02
Restricted PoC
Airports and industrial parks.
03
City integration
Link to city traffic systems.
04
Full City OS
Citywide autonomous control.
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