Inside TomTom's traffic products: Origin Destination Analysis

Whether your goal is to improve public transport scheduling or pick the right spot for a new business, TomTom Origin Destination (O/D) Analysis helps users analyze drivers’ preferred routes and trip patterns, so they can make smarter, location-based decisions.

Every day, drivers make journeys to and from different destinations. They might be commuting to the office, making last-mile deliveries, venturing into the city for a date or chauffeuring passengers to the airport. When all these trips are tallied up and tracked over time, fascinating pictures start to emerge from these trips. They can reveal traffic hotspots, the best place to add a new bus route, the perfect location for an advertising billboard and much more.

For those looking to gain deeper insights into how drivers move between different locations, there’s a good chance that they’ll be able to find them with TomTom Origin Destination (O/D) Analysis. The tool combs through vast volumes of traffic data to reveal detailed information about traffic flow and trip distributions within, between and across regions. In this article, we take a closer look at how TomTom’s solution works its analytical magic.

Why origin-destination analysis matters

Every journey has a start and end point – or an origin and a destination. When you analyze vehicle movements between pairs of geographic locations, especially at scale, you can uncover interesting patterns about traffic flows, commonly traveled routes, commuting behavior and more.

This information is useful for all kinds of sectors. It can be used by traffic authorities to re-design highways to deal with congestion, by urban planners to determine the best way to phase infrastructure works to minimize impact on road users or by logistics companies to understand how drivers and freight move between city, municipality and state borders.

Yet, for a long time, the only way to capture origin-destination data was with manual survey methods (like traffic light and roadside questionnaires) or with expensive hardware systems — both of which only offered a limited view of mobility patterns. What’s more, the surveys were time-consuming to administer, while the hardware systems used for activities like automated number plate recognition were expensive and complicated to install and maintain.

With the rise of cellphones, it became possible to use phone positioning data to collect location-based data on a much larger scale. But this information could only offer an approximate idea of travel patterns and trip distributions and was still time-consuming to collect and analyze.

A solution made to overcome these limitations

In contrast to the origin-destination analysis methods that came before it, TomTom O/D Analysis combines advanced analytics and data visualization, all powered by a big data archive. With O/D Analysis, users can explore travel patterns between origins and destinations in just a few clicks, without the need for surveys, hardware systems or deep statistical know-how.

To create the foundational database of O/D Analysis, TomTom gathers real-time Floating Car Data (FCD) from its network of more than 600 million connected devices, including vehicles and smartphones. FCD includes anonymized, time-stamped geolocation and speed information captured directly from moving vehicles, providing a definitive view of how real vehicles are moving on real roads all over the world.

By analyzing the sequence of location traces that originate from an individual device, TomTom’s algorithms can recognize the pattern of a trip between two points. It uses this information to define a trip between a specific origin and destination. The solution does this for millions of connected devices, building up a comprehensive picture of trip distributions within and across regions.

All FCD data is fully anonymized, preventing individual devices from being associated with specific drivers or people. Similarly, the origins and destinations are always associated with polygons (broader areas such as cities, districts, neighborhoods, postal codes and so on), not individual addresses like homes, apartment buildings or offices. This means they cannot be linked to a specific residence or businesses, further protecting privacy.

O/D Analysis is available as a RESTful API, ready for integration with organizations’ existing analytics platforms and business systems. The solution is also accessible via the TomTom MOVE portal, where customers can access rich data visualizations and analytics tools, plus step-by-step guides on different product features, reporting functionality and more.

With O/D Analysis, users can look at trip data from the last two years, with a moving time window. It means that, at the time of writing, users could include data as far back as October 2022. And if someone is using the tool in January 2025, they can analyze data going back to January 2023.

Bringing big data to life with rich analysis and reporting

O/D Analysis offers a straightforward process for setting up and running analyses. Users simply follow four key steps:

1. Defining the regions of the analysis. This can be done by importing an existing location dataset or adding the regions in the tool itself, either by selecting specific administrative areas (cities, districts or neighborhoods) on TomTom’s map or defining custom areas by drawing them on the map.

2. Defining the date ranges

3. Defining the time periods

4. Setting additional parameters and running the analysis.

Once processing is complete, O/D Analysis offers five different ways to explore the results. The first is Map Flows, an interactive view that allows users to visualize trip dynamics between different regions on a map.

Using Map Flows to visualize the volume of journeys between specific origin and destination regions.

The Matrix option shows all trip connections between different regions in the form of a table. Users can also see the regions that trips passed through on their way from an origin point to a destination point.

The Matrix view provides detailed information on trips made between a large number of origin and destinaiton points.

There’s also a Sankey Diagram view, which displays the number of connections between different regions in the form of lines. By default, this visualization shows the four regions with the highest number of trips measured. For users wanting to compare a larger number of regions, the Spatial Sankey view can be used to display the results in a map view, which makes it much easier to recognize dense flows between regions.

Visulaizing trips between different origins and destinations with a Sankey diagram.

Yet another option is Flows Explorer, an interactive report view that allows users to select and compare more than one origin, via and destination. In this view, users can also view certain trip statistics, including trip duration, length and hour of day.

Analyzing trip dynamics for multiple origin and destination points in the Flows Explorer view.

Most recently, TomTom introduced the Selected Link analysis feature, designed to analyze inbound and outbound trips in a selected area. Once users have defined a region of interest (referred to as a link), the tool will calculate the distribution of all trips on consecutive road segments within 10 km of the link.

Kamil Nowacki, Senior Quality Specialist for TomTom Traffic Analytics products, describes an inventive use case for this feature: “We have a customer who was looking at developing a flying taxi service. They used Selected Link in O/D Analysis to look at trip distributions between key points of interest, like airports and malls, in a specific city. After highlighting the most popular routes, they analyzed how long it took to travel along them by car. The customer then compared that journey time to the average time it would take a flying taxi to travel the same route — which was obviously significantly faster. This allowed them to put together a quantified business case for the flying taxi service, with hard figures for the improvements it could bring to journey times.”

Supporting a diverse array of applications

With O/D Analysis, the sky is truly the limit when it comes to mobility analysis. The solution provides valuable insights that can be applied across a range of sectors, from urban planning and traffic management to geomarketing and retail.

Urban planners and municipalities can harness O/D Analysis to map the most-used routes and study traffic flow between popular points of interest, building a better understanding of how people move and shaping smarter mobility options in response.

Consider a county government, who wants to modernize its network of bridges while minimizing impact on road users. With O/D Analysis, it’s possible to see how much traffic travels over each bridge in the county and draw up a plan of works that targets the least-used bridges for maintenance first, to reduce traffic disruption.

The analysis might reveal that 20% of all trips throughout the county pass over one main bridge. The government can phase infrastructure works to ensure that nearby bridges are left open when maintenance happens on this main bridge, so that traffic doesn’t increase exponentially, and drivers don’t need to make long detours.

What’s more, an advertising agency could use the same insight to determine the best location for a new outdoor campaign. It would be ideal to place banners on the bridge with the most appropriate traffic, ensuring that the campaign reaches the best audience.

This is just a small glimpse into the vast potential of O/D Analysis. Offering an impressive breadth and depth of analytical power and insight, TomTom’s solution holds huge power for improving the way we all move.

“Out of all TomTom’s Traffic Analytics tools, O/D Analysis probably is the most complex in terms of what it offers users,” concludes Kamil Nowacki. “It’s a sandbox where people are free to explore mobility data in many different ways and reveal interesting patterns of movement in the process.”