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The mystery of travel time accuracy debunked

This article was originally published on the TomTom Blog in February 2021. To read the full story, click here.

No matter if it’s a just-in-time delivery, or a just-in-time arrival for the kids’ football game, we all depend on accurate travel time calculations to make sure we arrive on schedule. But how do you keep those predictions up to speed?

In 2020, traffic all but disappeared from our roads — and it looks like it’s going to take some time for congestion to get back to normal levels. But what exactly does “normal” mean? Unfortunately, it’s congestion levels that continue to rise year-on-year. With more vehicles on the road and more people living in cities, urban congestion is only expected to get worse.

Urban congestion levels from the last 3 years, as measured by TomTom’s traffic data from 416 countries worldwide.

More congested roadways bring with them a host of issues, including ever-increasing travel times. It’s no wonder, then, that both commuters and commercial drivers are seeking solutions that predict travel times and find more efficient routes to their destinations. Travel time accuracy is more important than ever — whether you want to arrive home in time for dinner after a day at the office or if you’re delivering urgent medical supplies to a hospital a day’s journey away.

Real-time traffic: the first piece in the travel time puzzle

In order to predict accurate travel times and estimated times of arrival (ETAs), we need to know the road ahead — quite literally. TomTom has made that the center of its business. Every day, the company gathers more than 61 billion anonymous data points from our network of more than 660 million connected GPS devices. It uses this to update its real-time traffic service every 30 seconds, providing drivers with the freshest information on pretty much any route, covering more than 70 million driving hours a day in all.

But real-time data isn’t always enough — especially if you’re looking to calculate your arrival time for longer trips, and if you are planning journeys hours or even days in advance. Look at it this way: you’re planning to drive from Paris to Brussels, meaning you have an approximately 3.5-hour drive in front of you. Does it help you to know how bad traffic is in Brussels right now, if you’re going to be there in a couple of hours — when traffic will most likely have changed significantly?

For routing engines to calculate travel times and predict ETAs with true accuracy, they need something more than real-time traffic information. That’s where historical data and TomTom Speed Profiles come in.

TomTom has been collecting real-time traffic information for more than a decade. And uses this information to build a massive historical traffic database, complete with average travel times and speeds on individual road segments, for every day and time of the week and even per direction of traffic. It’s this treasure trove of traffic and speed information that forms the basis of TomTom Speed Profiles: the secret sauce behind our incredibly accurate travel time and ETA calculations.

By analyzing typical driving speed patterns, TomTom Speed Profiles enables routing engines in navigation applications to calculate accurate journey times based on real measured speeds — ensuring drivers get the optimal time-dependent route recommendation. TomTom Speed Profiles delivers typical speeds, such as those observed in everyday rush hours or in free-flow traffic at quieter times, while real-time traffic data covers unforeseen speeds and delays, such as those caused by a one-off traffic accident. Put together, this historical and real-time data allows routing engines to make highly precise arrival time predictions and even suggest alternative routes or times to travel.

Visualization of TomTom Speed Profiles data, showing real driving speeds recorded on one highway across different times of the day and different days of the week.

Take the above image, for example: you are looking at typical speed patterns from TomTom Speed Profiles Extended. Trillions of anonymous GPS-data points give speed insights on a specific stretch of road for every day of the week. You can clearly spot the Monday to Friday morning peaks, and especially afternoon rush-hours with their typical low speed due to traffic congestion.

Multiple formats for every need

TomTom Speed Profiles are delivered as convenient datasets, designed for easy integration and available in multiple formats:

  • Compact: with a small data footprint, optimized for on-device routing applications.
  • Extended: with highly detailed data that captures even the most exotic and unusual traffic patterns, optimized for online routing applications.

With TomTom Speed Profiles Compact, customers get ETA quality and accuracy unlike any other. What’s more, TomTom can deliver this in over 80 countries worldwide, which is unique in the market. The newly added TomTom Speed Profiles Extended builds on that strong foundation, offering customers even greater precision with improvements in ETA accuracy of up to 15% compared to the Compact version. TomTom Speed Profiles Extended is optimized for online navigation use cases, in line with the automotive industry moving towards ‘online first’ navigation — guaranteeing a best-in-class user experience.

TomTom wants everyone to have ETAs they can count on. That’s why the company has integrated TomTom Speed Profiles into its TomTom Traffic product, further increasing its overall precision. Speed Profiles also forms a cornerstone of in-vehicle navigation solutions and can be found in vehicles all over the world. With first-class routing technology helping us better predict the road ahead, the path is clear towards a future of gaining back time through smart travel time calculations.

Story by Liv Meinck, Senior manager product marketing
Edited by Matthew Beedham, Editor

Originally published at https://www.tomtom.com.

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We are the leading independent location technology specialist, shaping mobility with highly accurate maps, navigation, real-time traffic info and services.

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