Real-time data for traffic management and traffic planning
Mr. Schäfer, the collection and processing of digital data is considered one of the keys to the success of the transport revolution. Where do we stand in this respect?
We are already very far along in this respect. Our company, for example, can monitor up to 30% of real-time traffic in around 80 countries. This is due to the high scalability of the data and, of course, the high and constantly growing number of rolling data sources. This is helped by partnerships with companies in smartphone apps and mapping applications, fleet management solutions and fixed installations for cars and trucks. I once started with 200 cabs in Berlin. We're now up to 600 million vehicles worldwide.
How do you generate this data?
The system we rolled out many years ago is based on floating car data, which essentially comes from navigation and fleet management. As the market leader in traffic information, TomTom can be found in many built-in devices, including all the major German manufacturers, as well as other European and Asian manufacturers. And from this huge community, the users also send information back to us. In this way, we receive anonymized parameters, such as speed, location, etc.
What is the main benefit for the traffic turnaround?
The decisive factor for the traffic turnaround is that the public sector has also been moving toward digitalization for several years - by this I mean primarily the areas of traffic planning and management. Compared to industry, it's still a fairly gradual process, but it's making recognizable progress. For decades, traffic management authorities had relied on the use of road infrastructure to measure traffic flow, with data essentially only available on highways and major arterial roads.
What exactly do you mean by infrastructure?
I'm referring to conventional traffic measurement infrastructure, consisting of a variety of cameras, induction loops, infrared sensors, etc. Today, there is less and less reliance on this to measure traffic flow. Such an infrastructure is expensive to build and maintain, and it is far from providing all the relevant answers. Against this background, more and more traffic planning and management authorities are recognizing the need for a collaborative model and are buying the relevant data from us or from the competition and linking it to existing data.
Without fear of the transparent motorist?
At TomTom, we don't sell personalized measurement data, only derivations such as speed. It is about collective information, not the data of individuals. We don't focus on the fish, but always on the swarm. The goal is for the community to benefit, for example through fewer traffic jams.
Which authorities are already using such data?
One of the first, for example, was the Berlin Traffic Center. They started the project more than ten years ago. In Germany, Düsseldorf and Frankfurt am Main, among others, also use TomTom traffic data for traffic management and planning via partners such as GEVAS and PTV. The newly founded Autobahn GmbH has also decided to do so: The trend towards using vehicle-based traffic data is clearly visible. And this is not surprising, because the advantages are obvious.
What are they - apart from the cost savings you mentioned?
The data generated in this way provides much better information on which to base much better decisions. Where is the traffic jam in city XY? Where do I have the most annoying traffic jam in the morning? How should I plan my actions to have the best effect? For decades, federal transportation planning was based on induction loops and simulations. Today, we have area-wide traffic data in real time.
So simulations are superfluous?
When it comes to the current status quo, yes. After all, the data shows where the system is currently running and where things are going wrong. Even flashbacks are no problem. However, simulations still have their place when it comes to predictions or concrete solutions to calculate future scenarios, e.g., to evaluate construction measures to solve traffic problems.
Anyone who is stuck in a traffic jam every morning in any major city probably wishes for an extra lane ...
But from the point of view of those responsible, that should not be the solution. Traffic jams occur when capacity is less than demand. This can be seen at every rush hour or - on the highway - during vacations. Simply building new infrastructure is the wrong approach, because more infrastructure also increases demand. Instead, you have to think about what modal split you want to have in your city. This is a political planning aspect. It has something to do with the shift from road to other modes of transport. And we can also help with this with our data: We make it understandable where the greatest traffic demand is and where the "bottlenecks" are. To do this, you no longer have to put a pensioner at the intersection to count the cars.
So far, we have only talked about cars as data sources. What about other modes of transport?
E-bikes, scooters, etc. will also increasingly provide data. We're seeing a highly exciting development there right now. The growth in cycling in particular is phenomenal. In Copenhagen, there are already projects to prevent traffic jams - and by that I mean bicycle jams ...
TomTom and traffic light specialist Swarco are cooperating to supply the "My City" platform with traffic data. What is this all about?
This involves using data to monitor and control traffic in cities. Here, TomTom's vehicle-based traffic data supplements existing infrastructure measurements in front of intersections with valuable additional information.
What happens when the road network is simply overloaded?
Then at least some transparency can be created by displaying the congestion in navigation systems and calculating the expected delay. In the other case, i.e. if there is still capacity in the network, certain roads can be prioritized or better alternative route recommendations can be made via navigation.
Another cooperation was announced earlier this year. TomTom, together with Amazon Web Services (AWS), Meta and Microsoft, is founding the Overture Maps Foundation, led by the Linux Foundation, with the goal of developing interoperable open map data. What is this specifically about?
Mapping the physical world for more and more use cases is an extremely complex challenge that no single organization can tackle alone. The industry must come together to accomplish this task for the mutual benefit of all.
The goal of the Overture Maps Foundation is to build a high-quality, open map database that supports mapping applications for a wide range of industries.
Specifically, the goal is to provide a universal, open map framework based on a global standard. It aims to enable all stakeholders to easily exchange data and establish an ecosystem to share map data in an efficient way.
To do this, for example, the Overture Maps Foundation defines a common, well-structured and documented data schema and actively drives its adoption and dissemination. It also facilitates interoperability by providing a system that links entities from different datasets to the same real-world entities. To support professional applications as well, a sophisticated and extensive validation process has been installed to detect map errors, breaks, and deliberate misreporting, and to ensure that map data is as free of errors as possible.
The mission of the Overture Maps Foundation is fully in line with our vision at TomTom that the world needs an open and collaborative ecosystem to create up-to-date, accurate and reliable maps on a global scale. It is important to understand that the Overture Maps Foundation is working collectively on a shared basemap or database of map data - the goal is not to deliver a finished map product. Rather, the aim is to provide developers with the best possible basis on which to build their own industry- and case-specific solutions, e.g. for search or route planning, for navigation, for the display of traffic information or for the digital cockpit for car manufacturers.
The special charm of the Overture Maps Foundation model is that it is open to companies, NGOs, researchers, governments and other organizations, and with each new member and contributor, the quality of the database will continue to improve as the sources expand - and thus the base map automatically becomes interesting for further users and contributors. TomTom speaks in this context of a flywheel that gains speed with each new member.
What is your forecast: Will we still need traffic lights, gantries, etc. at some point?
This infrastructure would actually be superfluous in the case of nationwide autonomous driving: Every vehicle would be connected to every one, everything would be synchronized. But that's looking very far ahead, of course.
Allow me one last science fiction question: Wouldn't removing the human factor from driving, i.e. tailgating, playing with the gas, etc., result in a particularly large climate protection effect?
If we were all driving autonomous vehicles, that would be true. Then, for example, many more vehicles could use the green phase at a traffic light intersection. The big challenge is likely to be in the transition period, in other words, in mixed operation. This is because the distance control systems already in use strictly comply with the legal requirements. People often act a little more briskly, leaving fewer gaps in traffic. More of this kind of distance technology is therefore likely to lead to more traffic jams at first.
Thank you very much for the interesting interview.
has been responsible for the global product portfolio in the area of traffic and travel information systems as well as routing at TomTom since 2021. Since joining TomTom in 2006, Schäfer, who holds a degree in electrical engineering, has held various leadership positions within the company in the research and development of navigation and traffic products based on GPS data. Among other things, Schäfer and his team developed the globally established traffic information system for TomTom's navigation software as well as third-party navigation solutions in the field of built-in navigation solutions in cars and trucks, fleet management and smartphone applications. Ralf-Peter Schäfer worked in various research institutions such as the German Academy of Sciences, the German Center for Informatics and the German Aerospace Center (DLR) before joining TomTom.