Highways that think, adapt, and respond — in real time.
Geomatway continuously collects and analyzes real-time data from vehicles, road conditions, and driver behavior. This enables continuous visibility across the entire network — identifying patterns, detecting anomalies, and informing system-wide decisions in milliseconds.
Rather than reacting to congestion, Geomatway forecasts it using live and historical data. The system dynamically adjusts speed limits, lane priorities, and flow rules in advance — minimizing delays and preventing buildup before it starts.
Traditional systems ignore road shape. Geomatway incorporates curves, gradients, lane width, and merging zones into its decision engine — optimizing how traffic moves based on the natural design of each segment.
The platform responds automatically to weather conditions like fog, rain, dust storms, or poor visibility — adjusting speed zones, driver alerts, and traffic behavior based on real-time environmental feedback.
Geomatway links surveillance, vehicle input, and control systems. It detects incidents instantly and triggers automated responses — rerouting traffic, reducing speed, or alerting nearby vehicles in seconds.
Instead of rebuilding roads, Geomatway adds a digital, modular layer that integrates with existing infrastructure. It’s cost-effective, easily deployed in phases, and designed to scale across cities, regions, or national networks.
Geomatway integrates the human dimension of driving into its decision-making engine. It interprets real-time behaviors like overtaking, tailgating, and late merging, while also learning from long-term trends across corridors and time windows. This behavioral intelligence enables more culturally aware, risk-adjusted, and responsive traffic control.
