PTV unveils predictive, machine-learning tool for real-time traffic management


PTV Group, part of Umovity, has announced the launch of PTV Flows, a cloud-based tool which can forecast congestion up to two hours in advance, using machine learning.

PTV Flows enables cities and road authorities to proactively manage traffic flows even without access to advanced traffic management infrastructures or detectors.

The software tool uses maps and floating car data from major providers such as TomTom that are updated automatically. It can be easily and flexibly adapted to different user needs. Installation is hassle-free as PTV Flows operates directly from a browser or can be seamlessly integrated via API into existing systems.

The tool analyzes historical and current speeds as well as specific KPIs monitoring zones or corridors. By identifying patterns and trends, the self-learning system generates forecasts for the next 30 to 120 minutes.

Automatic and predictive alerts enable traffic operators to anticipate potential issues and take proactive measures to mitigate congestion. Additionally, relevant stakeholders, including law enforcement agencies, can receive immediate notifications.

Apart for the traffic management centers, the tool can be used for a wide range of use cases such as real-time monitoring of construction sites or evaluating the network performance of motorways or automation activation of traffic schemes using the predictive alerts.

“Following the successful launches of PTV Access and PTV Lines, we are delighted to introduce the latest addition to our data-driven SaaS product portfolio: PTV Flows has been designed with cities and road authorities in mind that don’t have the time or the resources to set up and maintain an advanced traffic management infrastructure,” says Christian U Haas, CEO of PTV Group. “This new lightweight tool will change their daily work. PTV Flows not only empowers operators to proactively manage traffic, reducing delays and enhancing safety, but also improves overall transport system efficiency.”

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About Author


Tom has edited Traffic Technology International (TTi) magazine and its Traffic Technology Today website since May 2014. During his time at the title, he has interviewed some of the top transportation chiefs at public agencies around the world as well as CEOs of leading multinationals and ground-breaking start-ups. Tom's earlier career saw him working on some the UK's leading consumer magazine titles. He has a law degree from the London School of Economics (LSE).