Bengaluru Traffic Police embrace AI to catch violators, manage congestion

Gone are the days of relying on the physical presence of traffic police to enforce rules in Bengaluru. The city's traffic police have embraced artificial intelligence (AI) to monitor and manage traffic violations, transforming the way road safety is enforced.

Bengaluru is expanding its AI-driven traffic enforcement system to detect 13 different violations, up from the current seven. New additions include wrong-side driving, illegal number plates, overloaded goods vehicles, faulty mirrors, and illegal parking.

"At present, we use AI-based cameras to enforce seven violations," said MN Anucheth, Joint Commissioner of Police (Bengaluru City Traffic). "We will soon expand to cover 13 types of violations," he added.

Currently, 330 AI-powered cameras monitor 50 junctions, and that number is expected to increase as the system expands.

Bengaluru's AI system utilises Automatic Number Plate Recognition (ANPR) and can process video feeds from various sources, including surveillance cameras, body-worn cameras, and even social media.

“Instead of procuring additional cameras, we decided to obtain AI-based automatic violation detection licences to utilise our existing infrastructure for traffic enforcement and management," Anucheth explained.

In 2023, Bengaluru Traffic Police booked nearly 9 million cases and collected a record Rs. 185.1 crore in fines, primarily through contactless enforcement. These figures are expected to rise significantly with the expanded AI system.

Beyond Enforcement: AI for Traffic Management

Bengaluru's AI system isn't limited to catching violators. It also helps manage traffic flow and improve road safety:

Detecting Hazards: Identifies waterlogged areas, stray animals, potholes, and unattended objects.

Optimising Traffic Signals: Automatically adjusts traffic light timings based on real-time conditions, reducing congestion and bottlenecks.

Automatic Traffic Counting and Classification (ATCC): Monitors vehicle types at different junctions to provide insights for better traffic management.