By now the industry agrees that HD maps are needed for autonomous driving. Cars need to position themselves very accurately and be aware of the road ahead in order to plan their next move. In this panel session on HD mapping, three map companies will talk about how they are building HD maps in different regions of the world and how to automate map making using AI. But even more important, how will they keep their HD maps up to date? After all, an out of date HD map will not help the car. The panel will also touch on how cars should access the latest, most up-to-date HD maps with minimal latency.
Autonomous vehicles require highly accurate, up-to-date maps for a safe, comfortable and optimized experience. TomTom's multi-source, multi-sensor approach leads to HD Maps that have greater coverage, are more richly attributed, and have higher quality than single-source, single-sensor maps. Autonomous vehicles also need to be able to access the latest, most up-to-date HD Maps with minimal latency. Learn how TomTom is taking on this challenge.
TomTom is leading in HD Maps in coverage and number of OEMs working with our HD Map. Our multi-source, multi-sensor approach leads to HD maps that have greater coverage, are more richly attributed, and have higher quality than single-source, single-sensor maps. Hear how were weaving in more and more sources, such as AI-intensive video processing, into our map making to accelerate towards our goal of real-time and highly precise maps for safer and more comfortable driving.
It's simple to take the output of one type of sensor in multiple cars and produce a map based on that data. However, a map created in this way will not have sufficient coverage, attribution, or quality for autonomous driving. Our multi-source, multi-sensor approach leads to HD maps that have greater coverage, are more richly attributed, and have higher quality than single-source, single-sensor maps. In this session, we will discuss how we have created the world's largest HD map, are able to continuously update it, and are making autonomous driving safer and more comfortable.
Hear the latest thinking on the maps that autonomous cars will use for highly accurate positioning. Autonomous cars need maps to function. The most critical use of maps is centimeter-level positioning. TomTom solves this with highly accurate lane information and lateral depth maps, which we call RoadDNA. Autonomous driving and map creation have incredible synergy. Mobile mapping cars go through the exact same process as autonomous cars: sensor perception, sensor data processing and comparing it with a stored version of reality. We process the sensor data with GPUs for fast creation of deep neural networks (DNNs) that can recognize traffic signs and other road attributes, both in-car as well as in the cloud. These DNNs, RoadDNA and sensors in the car together enable autonomous cars.