New app applies machine learning to travel planning


A US-based traffic information company claims to have built the first-ever mobile app that uses machine learning techniques to help motorists reach their destinations as quickly and efficiently as possible.

Inrix Traffic, released on March 30th for Android and iOS devices, is described by developers Inrix as a “next-generation navigation and traffic app” that “learns user preferences to take the guesswork out of driving”.

Unlike similar apps that rely entirely on publicly available traffic data to estimate journey times and plan optimal routes, Inrix Traffic is designed to build up a picture of a user’s own particular driving habits to predict and personalise routes.

Its features include the ability to compile a list of the user’s “favourite places” – such as home and work – automatically, saving them time that would otherwise be spent inputting them by hand; the ability to predict trips based on previous activity and adhering to the driver’s preferred routes; and integration with the mobile device’s built-in calendar.

As for the underlying traffic data, this comes from a massive crowd-sourced network of over 275 million connected cars and devices, which Inrix claims to offer “the most accurate map and real-time information in the world”.

Commenting on the launch, the company’s president and chief executive Bryan Mistele said: “Users want an app that is accurate, personalised and smart enough to work proactively for them – so we’ve integrated several highly advanced technologies into one all-encompassing app.”

He added that Inrix Traffic delivers “the most cutting-edge technology available in a nav app today”.

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