Many local and national authorities have developed data feeds announcing road closures, roadworks, accidents and other r

TomTom Traffic Incidents: Provides precise locations and delays caused by congestion on the road network, allowing routing programs to provide the fastest route based on actual current travel times

By collecting FCD, TomTom creates and maintains an anonymous archive with actual driven trips for analysis purposes. The ability to map-match and analyze large volumes of data allows TomTom to make traffic predictions at scale. No matter how small or large the road network, the data can produce accurate traffic predictions throughout the day.

TomTom’s traffic fusion engine calculates congestion and delays based on defined free flow traffic thresholds and speed profiles with 3.5 billion kilometers of live trip data collected globally every day. The equivalent of 70 billion driving hours, this provides an extremely detailed predictive traffic baseline for every road, for every day of the week, for every 5-minute interval.

TomTom uses this road data wherever possible and provides an option for authorities and trusted partners to directly input this information into TomTom Traffic Information services.

TomTom exploits different techniques to obtain high quality predictions of traffic, ranging from simple heuristics to statistical methods, traffic simulations and machine learning models. To this end, our traffic engineering teams collaborate with traffic statistics and data science teams who have strong geospatial research backgrounds. Besides predicting drivable speeds for the future, we also predict the occurrence of future jams and how existing jams will evolve over time.

The video below illustrates our jam evolution prediction, which makes use of machine learning models using criteria such as flows into and out of the jam, detected jam front velocities and many others. The combination of top experts in the industry, an abundant amount of traffic data and advanced machine learning technologies allows us to produce the most reliable traffic predictions.

A representation of a time-distance plot chart with color grading reflecting vehicle speeds (red means low speeds). The chart evidences the need for high-resolution probe data to accurately identify heads and tails of jams accurately and timely.

Think about it. In elementary school, if someone was mean to us, our parents told us the other kid acted that ay because they “liked us.” That teasing and name-calling was a normal form of showing your attraction.

The video shows the performance of a TomTom Traffic prediction visualized in a time-distance plot [F. Wendler et al. A method, apparatus and computer program for generating traffic jam data for a digital map. UK Patent 1918934.9., filed December 20, 2019].

TomTom Traffic Flow: Delivers a real-time, detailed view of traffic speeds on the entire road network, designed for easy integration into traffic management systems or routing engines to calculate current travel times

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TomTom sources incident data such as road closures and roadworks from trusted 3rd party sources including governmental entities and community input from millions of connected TomTom devices. Internal moderation teams also operate around the world to validate and moderate critical local road reports. On top of this data, TomTom Traffic makes use of weather information and holiday and local event information.

TomTom’s fusion engine intelligently combines the data from all available sources every 30 seconds into a database with traffic flow and incident data for the entire road network.

TomTom Traffic provides accurate information about traffic jams and expected delays on a planned route, helping drivers make better decisions that save time, reduce stress and make roads safer. It is an accurate, real-time service, driven by more than 600 million connected devices, that collects data on over 3.5 billion km of roadways per day.