Artificial Intelligence Eliminates Bus Stop Queues in Russia
A real-time computer vision system is transforming public transport efficiency and reducing waiting times across Moscow’s suburbs.
In the Moscow region, artificial intelligence has helped eliminate massive queues at bus stops. The system analyzed passenger flow data and identified key congestion points, enabling transport operators to adjust schedules and relieve pressure at 19 of the busiest locations.
The innovative project relies on cameras from the 'Safe Region' surveillance network. A specially trained neural network processes the video feed 24/7, automatically counting the number of people waiting. This information is fed into the Regional Management Center’s analytical system. When the AI detects sustained crowding, it automatically notifies operators, prompting them to increase bus frequency during peak hours.
AI to the Rescue of Public Transport
Currently, the system is active at 119 stops equipped with 114 cameras. Its accuracy in detecting congestion hotspots reaches 95 percent — a sign of how dependable and effective the approach is for daily use.
The project holds significance not only for Russia but for the global transport sector as well. It shows how digital transformation and advanced technologies can solve real-world challenges for millions of commuters, making urban environments more efficient and comfortable. The success of Moscow’s suburbs offers a scalable model that cities worldwide could adopt to tackle public transport overload in a smart and cost-effective way.
