rideOS + TomTom = Real-time traffic data for self-driving vehicles
Today, onstage at TechCrunch Disrupt in San Francisco, TomTom officially announced our partnership. We’re thrilled to formalize our collaboration with TomTom, since they are a key ally in our mission to build the comprehensive technology needed to enable the global roll-out of self-driving fleets.
TomTom has some of the highest quality traffic probe data thanks to real-time traffic updates from millions of drivers around the world (including users of Uber and Apple Maps). They’ve made this anonymized data accessible through OpenLR, an open source project that provides dynamic location referencing. This database has been invaluable to us since the real-time data platform that enables our constraint-based routing system includes information on everyday driving scenarios such as construction zones, pedestrian activity, bicyclists, inclement weather, road closures, and, importantly, traffic.
Our self-driving fleet partners use a variety of different external or in-house maps, so we need to be able to integrate with every kind of map. Using TomTom’s world class data through OpenLR, we’ve managed to layer real-time traffic data at a lane level on top of any base map our partners choose to use, meaning we can provide our partners with highly detailed information such as which lanes of a road are impacted — a feature that is particularly useful to self-driving vehicles.
In addition to integrating TomTom’s traffic data with our platform, we will begin using TomTom’s Speed Profiles and other standard definition map features to improve our routing engine’s predictive analytics. Our services will also become compatible with TomTom’s high definition maps.
Working with TomTom ensures rideOS has the most accurate data, which enables us to be the most reliable coordinating layer for self-driving vehicles. We look forward to exploring additional opportunities to collaborate with them to accelerate self-driving at scale.
