TomTom’s Orbis Maps with 3D Lane geometry set new standards for mapping precision

For the first time, continuously updated lane-level precision maps — measured down to a centimeter — are available for roads around the world. This technology enables automakers to accelerate the introduction of automated driving capabilities.

TomTom’s Orbis Maps with 3D Lane geometry innovation provides valuable insights into traffic patterns and congestion levels – delivering a wealth of actionable insights for businesses, automakers and city planners.

Automotive Industries (AI) asked Cyril Leman, Global Head of Product Marketing at TomTom, what the main benefits are of Orbis Maps with 3D Lane geometry.

Leman: TomTom has completely redesigned the way of building maps, using open collaboration as the foundation. This strategy enables us to collect data from various sources and to deliver them in a fully standardized way, and to scale faster.

When it comes to the automotive industry, we are now able to support our customers globally with their rollout of automated driving functions. It is important that we have updated information on every road everywhere, because it is a global industry. This includes providing map content that helps drivers and automated vehicles to obey the rules of the road – simple things such as speed limitations and traffic signs. The goal is to support higher levels of automation.

Our collaboration with the likes of the Overture Maps Foundation – founded by TomTom, Meta, Microsoft and Amazon – provides TomTom with the time and resources to focus on developing value adding map layers. By complementing the vehicle sensor network, we enable the driver or autonomous system to see beyond the line of sight and radar.

This assists with humanizing the autonomous driving system, which is an important element. When customers are testing an ADAS solution, we want them to feel the car is driving the way they would. This will help create confidence in the system.

Another benefit is that the car needs to be precisely positioned through lane level accuracy. Beyond that, we need to be able to advise the driver or vehicle whether it is safe to overtake – there may be an accident with a lane closure 500 meters up ahead.

When it comes to knowing exactly in which lane the vehicle is and what maneuver can be engaged, GPS systems are not precise enough as they cannot position a vehicle down to centimeter precision.

We are achieving this through open collaboration, which enables us to automate the updating of maps by conflating multiple data sources from vehicles driving on the roads and satellite imagery.

AI: What are the benefits for logistics operators and urban planners?

Leman: This is a big focus for the company. The TomTom Traffic Index provides high quality information on average travel time and congestion levels of 500 cities across 62 countries on six  continents.

Urban planners need to overcome traffic congestion to improve the quality of life for people living in cities. TomTom has been leading the way for a long time by providing drivers with real time traffic information.

City planners can access analytics from the millions of connected devices TomTom has in the field and over 25 years of analytics which enables them to understand mobility patterns. They can, for example, determine what people are doing at a particular junction near an entertainment venue, and the impact of a major event.

Using this data, a city planner or city authority can forecast potential traffic jams and take the appropriate action to better orchestrate the traffic. Logistics operators can also plan their routes around the congestion.

AI: Was the approach to creating Orbis Maps radically different?

Leman: The traditional way of building a map is to populate it with your proprietary information using your own tooling, creating basically a private ecosystem to build the map. The challenge is that the world is changing constantly. It costs a lot to maintain the database, which is the road network. Even if you have thousands of people mapping their neighborhoods, you need to validate the information.

What we have done is combine the best of two worlds. Our proprietary map content has been merged with the live updates into one open standardized ecosystem, with all inputs sharing the same reference IDs. This allows the maps to be updated through over 10,000 edits on a daily basis. Propriety information about the infrastructure such as roads, bridges and buildings, provides the foundations on which you can build value.

TomTom Maps are also futureproof because they are updated as soon as the situation changes. This also ensures the level of quality required by our business and government customers.

AI: What does machine learning and artificial intelligence (AI) bring to TomTom maps and updates?

Leman: In a dynamic environment such as traffic, any changes on the ground need to be reflected in real time on the map. It is just not sustainable to do it all manually. While we still have manual editors, we have integrated their input with machine learning AI. The model is being trained to recognize patterns such as lane markings, junctions and specific road signs to automatically update the map.

This reduces the production cost of the map, but more importantly for our customers, it means that road conditions are updated in real time, wherever they are. Certain competitors focus on specific highways or cities. Our approach is to deliver a map on every road network, including secondary roads on a global basis.

AI: OEMs are always looking for flexibility and differentiation. Can the maps be tailored to meet specific customer needs?

Leman: Customization may mean different things. To state the obvious, mapping is all about data or content, right? We provide tools and services to enable our customers to access the data in order to personalize the maps.

We have programmers who, for instance, just want access to the map content, and they will build the software on their own. Other customers want a full navigation application using our mapping sites. Customers can add layers on top of our maps to tailor the content to their brand or for the needs of their customers. An example is an OEM which wants to retain electric vehicle (EV) drivers within their brand experience. They will prioritize their own charging points.

There can also be different layers, such as LiDAR to support driving at night or when there is limited visibility. TomTom believes it is important to allow their customers to create an experience that supports their brand ecosystem. They can fully customize the navigation to support and enhance their brand experience.

Their designers can change the full human machine interface (HMI) of the navigation system, including the shape and color of the buttons, font, and the look and feel of the map to make it fit seamlessly into the design of the cockpit.

AI: How crucial is the traffic data for organizations across various sectors?

Leman: Let us start by accepting that traffic is the lifeblood of cities and economies. TomTom was founded on the belief that connected devices can contribute to creating better traffic quality.

In Europe, about one out of four cars on the road feeds us data, which gives us access to tremendous amounts of anonymized insights which translate into traffic information that we take back to our customers so they can make informed decisions about the best route to take.

For industry and private drivers, every minute counts. You satisfy your customers because you arrive on time, or your fleet is more efficient because you gain a few minutes through intelligent routing.

If you are in your own vehicle, you want to make sure that you arrive on time for your next meeting or a family dinner.

City authorities want to ensure there are good synergies between pedestrians and drivers, and that they can optimize mobility by taking their traffic management system to the next level.

If you are fleet manager, the last 100 meters is as important as the rest of the journey. Drivers need to know how to avoid traffic congestion and where to park.

AI: What’s next for TomTom?

Leman: We see huge potential for automated driving to come of age. For it to realize its potential, the automotive industry needs access to map content with the level of quality and coverage we provide.

Then there is the emergence of the software defined vehicle, where there is a convergence between navigation and the driving experience. For that navigation, down to the lane level is a fundamental requirement.

There is also a need for geospatial analytics and more understanding of traffic patterns by urban planners. Analytic tools are needed to provide context because data without that does not mean anything. With analytics, we can support government agencies with more intelligence, insurance companies with more accurate information, cities with better traffic analytics and more.