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Moderator: Dr. Justyna Zander, Global Head of Mapping, NVIDIA This session will discuss NVIDIA DRIVE Mapping, a platform that enables vehicle manufacturers to use maps from various global providers for highly accurate navigation and localization. DRIVE Mapping products integrate a scalable sensor suite, software development kits, and co-integrated high-definition maps from leading mapping companies. These end-to-end technologies help collect environmental data to create and update HD maps. We'll explain how the platform makes it possible for a self-driving vehicle to localize itself with precision, discern potential hazards, and determine exactly where it can safely drive. Leaders from the mapping technology companies will discuss the advantages of various modalities of maps and the benefit they provide to autonomous vehicles, followed by a short Q&A session. TomTom: Willem Strijbosch, Head of Autonomous Driving Mapping Progress on the Car-to-Cloud-to-Car Cycle The talk will discuss the latest on map creation and using crowdsourced data for map updates at TomTom.  3DMapping: Dr. Gunnar Gräfe, CEO and Founder Precise Ultra HD Map Data as Basis for Virtual Testing and Simulation Digital road data is the basis for virtual testing and simulation. Artificially designed digital roads may help case by case, but for various applications the precise digitalization and digital as-built representation of real-world roads is needed. The typical requirement is, that the roads used for virtual testing and simulation are regarded as digital twin of the real-world roads, which is prerequisite for comparable testing in reality and in the virtual environment. The technical solution for digitizing test tracks, race tracks and public roads with sufficient accuracy and resolution is high-end mobile surveying using high-resolution scanners and multiple cameras. 3D Mapping has invented the necessary technology since more than 20 years and today deploys van-based survey systems worldwide. The technology is used for example to generate high-resolution digital road surface models in OpenCRG format or to produce precise high definition reference maps in OpenDrive format, which are either used for virtual simulation and testing or as reference map in the car for autonomous driving development. 3D Mapping is member of the OpenDrive core team and has been intensively working on standardization and updates of the formats OpenDrive and OpenCRG since several years and is fully engaged in the ongoing ASAM format standardizations. The developments lead to new standards including 3D environment combined with scenario elements.
Moderator: Dr. Justyna Zander, Global Head of Mapping, NVIDIA This session will discuss NVIDIA DRIVE Mapping, a platform that enables vehicle manufacturers to use maps from various global providers for highly accurate navigation and localization. DRIVE Mapping products integrate a scalable sensor suite, software development kits, and co-integrated high-definition maps from leading mapping companies. These end-to-end technologies help collect environmental data to create and update HD maps. We'll explain how the platform makes it possible for a self-driving vehicle to localize itself with precision, discern potential hazards, and determine exactly where it can safely drive. Leaders from the mapping technology companies will discuss the advantages of various modalities of maps and the benefit they provide to autonomous vehicles, followed by a short Q&A session. TomTom: Willem Strijbosch, Head of Autonomous Driving Mapping Progress on the Car-to-Cloud-to-Car Cycle The talk will discuss the latest on map creation and using crowdsourced data for map updates at TomTom.  3DMapping: Dr. Gunnar Gräfe, CEO and Founder Precise Ultra HD Map Data as Basis for Virtual Testing and Simulation Digital road data is the basis for virtual testing and simulation. Artificially designed digital roads may help case by case, but for various applications the precise digitalization and digital as-built representation of real-world roads is needed. The typical requirement is, that the roads used for virtual testing and simulation are regarded as digital twin of the real-world roads, which is prerequisite for comparable testing in reality and in the virtual environment. The technical solution for digitizing test tracks, race tracks and public roads with sufficient accuracy and resolution is high-end mobile surveying using high-resolution scanners and multiple cameras. 3D Mapping has invented the necessary technology since more than 20 years and today deploys van-based survey systems worldwide. The technology is used for example to generate high-resolution digital road surface models in OpenCRG format or to produce precise high definition reference maps in OpenDrive format, which are either used for virtual simulation and testing or as reference map in the car for autonomous driving development. 3D Mapping is member of the OpenDrive core team and has been intensively working on standardization and updates of the formats OpenDrive and OpenCRG since several years and is fully engaged in the ongoing ASAM format standardizations. The developments lead to new standards including 3D environment combined with scenario elements.  Back
 
Topics:
Autonomous Vehicles
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9771
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Abstract:

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.

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.

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Topics:
Autonomous Vehicles
Type:
Panel
Event:
GTC Europe
Year:
2018
Session ID:
E8469
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Abstract:

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.

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.

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Topics:
Autonomous Vehicles, HD Mapping
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8700
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Abstract:

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.

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.

  Back
 
Topics:
Autonomous Vehicles, HD Mapping
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23130
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Abstract:

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.  

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.  

  Back
 
Topics:
HD Mapping, Autonomous Vehicles
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7809
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Abstract:

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.

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.

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Topics:
Autonomous Vehicles, Artificial Intelligence and Deep Learning, Big Data Analytics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2016
Session ID:
S6849
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