Nvidia‘s accelerated computing has helped India manage its tollbooth traffic, which spans four million miles across 1,000 tollbooths.
Tne Indian road network is the second-largest in the world, and most of it is run manually. Traditional tollbooths, wherever in the world they’re deployed, can contribute to massive traffic delays, long commute times and serious road congestion.
To help automate tollbooths across India, Calsoft, an Indian-American technology company, helped implement a broad range of Nvidia technologies integrated with the country’s dominant payment system, known as the unified payments interface, or UPI, for a client.
Manual tollbooths demand more time and labor compared to automated ones. However, automating India’s toll systems faces an extra complication: the diverse range of license plates.
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India’s non-standardized plates pose a significant challenge to the accuracy of automatic number plate recognition (ANPR) systems. Any implementation would need to address these plate variations, which include divergent color, sizing, font styles and placement upon vehicles, as well as many different languages.
The solution Calsoft helped build automatically reads passing vehicle plates and charges the associated driver’s UPI account. This approach reduces the need for manual toll collection and is a massive step toward addressing traffic in the region.
Automation in Action
As part of a pilot program, this solution has been deployed in several leading metropolitan cities. The solution provides about 95% accuracy in its ability to read plates through the use of an ANPR pipeline that detects and classifies the plates as they roll through tollbooths.
Nvidia’s technology has been crucial in this effort, according to Vipin Shankar, senior vice president of technology at Calsoft. “Particularly challenging was night-time detection.
Another challenge was model accuracy improvement on pixel distortions due to environmental impacts like fog, heavy rains, reflections due to bright sunshine, dusty winds and more,” he said.
The solution uses Nvidia Metropolis to track and detect vehicles throughout the process. Metropolis is an application framework, a set of developer tools and a partner ecosystem that brings visual data and AI together to improve operational efficiency and safety across a range of industries.
Calsoft engineers used Nvidia Triton to deploy and manage their AI models. The team also used the Nvidia DeepStream software development kit to build a real-time streaming platform. This was key for processing and analyzing data streams efficiently, incorporating advanced capabilities such as real-time object detection and classification.
Calsoft uses Nvidia hardware, including Nvidia Jetson edge AI modules and Nvidia A100 Tensor Core GPUs in its AI solutions. Calsoft’s tollbooth solution is also scalable, meaning it’s designed to accommodate future growth and expansion needs, and can better ensure sustained performance and adaptability as traffic conditions evolve.