A New Level of Accident Detection

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