AI for Traffic Management

In the past, traffic violation monitoring systems have been simplistic in nature and were designed to overlook many of the violations that are common in today's fast-paced world. AI based traffic analytics is taking a different approach with a goal to truly understand how vehicles work.

A smarter system can capture and process various traffic violations such as red-light violations, illegal lane changes, triple riding, no helmet, speeding and more in the active area using the latest in Computer Vision techniques combined with Deep Learning techniques. The fact that this system captures all types of cars from every angle means it is able to capture subtle occurrences.

The advent of Artificial Intelligence (AI) has heralded radical advances in many sectors. From self-driving vehicles to the fight against cancer, AI is proving time and again its strength, versatility and applicability. What is very likely the most telling evidence of AI’s potential yet is the revolution it has brought to traffic management systems.

AI has become the technology of choice for traffic management systems. It provides a much-improved user experience and is fast becoming the norm. In many countries, licensing laws have been amended to enable driverless vehicles to operate on public roads. This shift has also seen attempts made to improve road safety and reduce accidents. Nevertheless, despite its promise in reducing traffic accidents, the implementation of AI into traffic management systems is still a cause for concern.

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