DRIVE Sim
Dec 18, 2023
Teaching AVs the Language of Human Driving Behavior with Trajeglish
Much of the communication between drivers goes beyond turn signals and brake lights. Motioning another car to proceed, looking over to see if another driver is...
5 MIN READ
Dec 05, 2023
Reconstructing Dynamic Driving Scenarios Using Self-Supervised Learning
From monotonous highways to routine neighborhood trips, driving is often uneventful. As a result, much of the training data for autonomous vehicle (AV)...
6 MIN READ
Nov 28, 2023
Simulating Realistic Traffic Behavior with a Bi-Level Imitation Learning AI Model
From last-minute cut-ins to impromptu U-turns, human drivers can be incredibly unpredictable. This unpredictability stems from the complex nature of human...
5 MIN READ
Nov 13, 2023
Using Synthetic Data to Address Novel Viewpoints for Autonomous Vehicle Perception
Autonomous vehicles (AV) come in all shapes and sizes, ranging from small passenger cars to multi-axle semi-trucks. However, a perception algorithm deployed on...
7 MIN READ
Sep 27, 2023
Free Course: Essentials of Developing Omniverse Kit Applications
Take this free self-paced course to learn how to leverage NVIDIA Omniverse Kit to easily build apps on the Omniverse platform.
1 MIN READ
Sep 26, 2023
Validating NVIDIA DRIVE Sim Radar Models
Sensor simulation is a critical tool to address the gaps in real-world data for autonomous vehicle (AV) development. However, it is only effective if sensor...
15 MIN READ
Jul 27, 2023
Sensing New Frontiers with Neural Lidar Fields for Autonomous Vehicle Simulation
Autonomous vehicle (AV) development requires massive amounts of sensor data for perception development. Developers typically get this data from two...
6 MIN READ
May 18, 2023
Bringing Far-Field Objects into Focus with Synthetic Data for Camera-Based AV Perception
Detecting far-field objects, such as vehicles that are more than 100 m away, is fundamental for automated driving systems to maneuver safely while operating on...
7 MIN READ
Feb 23, 2023
Generating AI-Based Potential Accident Scenarios for Autonomous Vehicles
Autonomous vehicles (AVs) must be able to safely handle any type of traffic scenario that could be encountered in the real world. This includes hazardous...
4 MIN READ
Jan 20, 2023
Validating NVIDIA DRIVE Sim Lidar Models
Autonomous vehicle development is all about scale. Engineers must collect and label massive amounts of data to train self-driving neural networks. This...
2 MIN READ
Jan 04, 2023
Upcoming Webinar: Transforming Transportation with the Metaverse and AI
Learn how NVIDIA Omniverse and NVIDIA DRIVE Sim are used to create digital twin environments to train, test, and validate autonomous driving systems.
1 MIN READ
Oct 28, 2022
Getting to Know Autonomous Vehicles
The future is autonomous, and AI is already transforming the transportation industry. But what exactly is an autonomous vehicle and how does it work? Autonomous...
5 MIN READ
Sep 21, 2022
New Cloud Applications, SimReady Assets, and Tools for NVIDIA Omniverse Developers Announced at GTC
Developers, creators, and enterprises around the world are using NVIDIA Omniverse to build virtual worlds and push the boundaries of the metaverse. Based on...
10 MIN READ
Jul 27, 2022
Closing the Sim2Real Gap with NVIDIA Isaac Sim and NVIDIA Isaac Replicator
Synthetic data is an important tool in training machine learning models for computer vision applications. Researchers from NVIDIA have introduced a structured...
10 MIN READ
Jun 27, 2022
Build Custom Synthetic Data Generation Pipelines with Omniverse Replicator
Companies providing synthetic data generation tools and services, as well as developers, can now build custom physically accurate synthetic data generation...
8 MIN READ
Dec 16, 2021
Validating NVIDIA DRIVE Sim Camera Models
Autonomous vehicles require large-scale development and testing in a wide range of scenarios before they can be deployed. Simulation can address these...
17 MIN READ