TomTom announced that its real-time and historical Traffic data, Speed Profiles, and map elements will be integrated into rideOS’ innovative routing platform for self-driving vehicles to improve predictive analytics.
rideOS has developed a platform that synthesises, manages, and distributes critical safety data and routes for any and every type of transport. It’s a crucial service for a future where multiple modes of transport, from human-operated to fully autonomous, will be sharing the roads.
Through this agreement, rideOS’ services will also become compatible with TomTom’s High Definition maps, and the two companies will explore additional opportunities together. The traffic component of rideOS’ data platform is provided by TomTom through OpenLR, an open source project that provides royalty-free dynamic location referencing to enable reliable data exchange.
Anders Truelsen, Managing Director of TomTom Enterprise, said: “The future of self-driving technology is dependent on mapping and navigation technologies. High-Definition maps, real-time and historical traffic data, live data from vehicle sensors, and more, must be filtered through a coordinating layer such as rideOS if we are to get past the hurdle of self-driving and human-operated vehicles driving side-by-side.”
Chris Blumenberg, CTO and co-founder of rideOS, comments: “Working with TomTom ensures that rideOS has highly accurate data, which enables us to be the most reliable coordinating layer for self-driving vehicles. Not only are they a trusted partner that shares our vision for the future, but they have also provided us with the highest-quality real-time traffic data, which has been integral to our constraint-based routing engine.”
TomTom sources real-time traffic updates from 550 million data points around the world, through an anonymous and mutually beneficial process.
Source and photo credits: TomTom