The TrafficData accident detection module successfully identifies road incidents. Updated TrafficData Macro algorithms have significantly improved the efficiency and accuracy of accident detection.
Key updates to the accident recognition algorithm:
Detection based on prolonged vehicle stoppage
The algorithm analyzes vehicle behavior over time and identifies atypical scenarios in which a vehicle remains stationary for an extended period. This is one of the key indicators of a potential traffic accident.
Background subtraction algorithm applied
A vehicle that remains stationary in the frame for a long time gradually becomes part of the background. This allows the system to reliably detect objects that fall outside the normal traffic flow.
Background images are fed into a neural model
Using the resulting images, the model recognizes and classifies the object as a traffic accident.
In Tyumen, the TrafficData Macro system already detects accidents simultaneously from two cameras at the same intersection, providing a more complete and accurate picture of incidents.
Over a year of operation, the updated module algorithm has demonstrated a multiple increase in key performance metrics and significantly improved accident detection accuracy compared to the previous version.
📎 Detailed information about TrafficData Macro and the accident detection module is available on the website