Redefining what is possible in Traffic detection
Hybrid AI Tracking represents the next step in intelligent traffic detection, combining radar-based detection and video-based detection into a single, fully integrated solution: Hybrid AI Tracking.
What Hybrid AI Tracking is
Hybrid AI Tracking is the next evolution in smart traffic detection.
The Hybrid AI Tracking combines high-definition video with radar sensors to enhance stop line vehicle detection at signalized intersections. This all-in-one, fully integrated solution enables safer and more efficient traffic flow and is optimized for fast deployment with minimal impact on infrastructure.
With Hybrid Sensor Fusion, high-performance AI algorithms fuse radar detection and add video detection. From traditional algorithms to artificial intelligence, the latest tracking algorithms running on powerful processors provide Super Resolution AI Tracking with radar-radar fusion and video.
The system tracks objects up to 300 meters away and provides accurate speed and position information. It enables accurate detection of vehicles, cyclists, and pedestrians in various conditions and supports excellent counting performance across many lanes. Hybrid AI Tracking works in all weather and lighting conditions and provides high-accuracy detection anytime and anywhere.
Why it will revolutionize radar usage in ITS
Hybrid AI Tracking brings a new level of accurate detection in Traffic Management by combining radar and video in one all-in-one, fully integrated solution. Radar’s long-range precision is combined with high-definition video and high-performance AI algorithms to improve traffic safety and efficiency, especially at intersections and for left-turn detection.
By increasing detection accuracy, enhancing stop line vehicle detection, and supporting safer and more efficient traffic flow at intersections, Hybrid AI Tracking sets a new standard for how radar is used in Intelligent Transportation Systems. It enables high-accuracy detection in many lanes, in all weather and lighting conditions, and with minimal impact on infrastructure during deployment.
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