Startup’s AI Intersects With U.S. Traffic Lights for Better Flow, Safety

Thousands of U.S. traffic lights may soon be getting the green light on AI for safer streets.

That’s because startup CVEDIA has designed better and faster vehicle and pedestrian detections to improve traffic flow and pedestrian safety for Cubic Transportation Systems. These new AI capabilities will be integrated into Cubic’s GRIDSMART Solution, a single-camera intersection detection and actuation technology solution used across the United States.

Cubic needs computer vision models trained with specialized datasets for its new pedestrian safety and traffic systems. But curating data and training models from scratch takes months, so they are partnered with CVEDIA for synthetic data and model development.

CVEDIA’s synthetic algorithm technology accelerates development of object detection and image classification networks. Adopting the NVIDIA Transfer Learning Toolkit has enabled it to further compress development time. The traffic light implementation for smarter intersections is now being deployed in more than 6,000 intersections spanning 49 states.

NVIDIA today released Transfer Learning Toolkit version 3.0 into general availability.

“By using NVIDIA Transfer Learning Toolkit, we cut model training time in half and achieved the same level of model accuracy and throughput performance,” said Rodrigo Orph, CTIO and co-founder of CVEDIA.

Metropolis Boosts Infrastructure

CVEDIA develops applications using NVIDIA Metropolis and is a member of NVIDIA Inception, a virtual accelerator program that helps startups in AI and data science get to market faster.

NVIDIA Metropolis is an application framework for smart infrastructure. It provides powerful developer tools, including the DeepStream SDK, Transfer Learning Toolkit, pre-trained models on NGC, and NVIDIA TensorRT.

Transfer learning is a deep learning technique that enables developers to tap a pre-trained AI model used on one task and customize it for use in another domain. NVIDIA Transfer Learning Toolkit is used to build custom, production quality models faster with no coding required.

“Safety is the most fundamental need for all drivers and vulnerable road users traveling through intersections. CVEDIA’s AI and synthetic data expertise allow us to both augment our existing AI models and rapidly iterate for new applications,” said Jeff Price, Vice President and General Manager of Cubic Transportation Systems’ ITS unit.

Signaling Smarter Intersections

Cubic’s GRIDSMART Solution  is using 360-degree view cameras to optimize traffic flow by gathering and interpreting important traffic data. GRIDSMART empowers traffic engineers to adjust signal timing and traffic flow strategies, and enables real-time monitoring and visual assessment.

For this new system, CVEDIA is developing image classification and object detection models to follow the movement of vehicles, people, bicycles, pets and other safety concerns in intersections.

“Cubic wants to detect dangerous areas in an intersection and dangerous areas where a pedestrian might cross, and they want to better control traffic,” said Rodrigo Orph.

Access the NVIDIA Transfer Learning Toolkit in general release availability.

Image courtesy of Aaron Sebastian on Unsplash.

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