NVIDIA AI for Autonomous Vehicles
GPTKB entity
Statements (74)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:AI_technology
|
| gptkbp:collaborated_with |
government agencies
non-profit organizations research institutions |
| gptkbp:collaborates_with |
automotive manufacturers
|
| gptkbp:contributes_to |
safety in transportation
|
| gptkbp:deployment |
commercial vehicles
|
| gptkbp:developed_by |
gptkb:NVIDIA_Corporation
urban mobility solutions |
| gptkbp:enables |
autonomous navigation
object detection |
| gptkbp:enhances |
computer vision capabilities
|
| gptkbp:exhibited_at |
industry conferences
|
| gptkbp:facilitates |
real-time decision making
|
| https://www.w3.org/2000/01/rdf-schema#label |
NVIDIA AI for Autonomous Vehicles
|
| gptkbp:improves |
path planning
|
| gptkbp:integrates_with |
gptkb:Eldar
|
| gptkbp:is_adopted_by |
ride-sharing companies
|
| gptkbp:is_based_on |
gptkb:NVIDIA_Drive_platform
|
| gptkbp:is_compatible_with |
various vehicle platforms
|
| gptkbp:is_connected_to |
internet of things (Io T) devices
|
| gptkbp:is_enhanced_by |
edge computing
big data analytics user experience design AI ethics guidelines augmented reality interfaces user interface innovations collaborative AI systems |
| gptkbp:is_evaluated_by |
regulatory bodies
real-world testing |
| gptkbp:is_influenced_by |
consumer demand for safety
machine learning advancements |
| gptkbp:is_integrated_with |
gptkb:smart_grid_technology
gptkb:mobile_applications vehicle-to-vehicle communication ADAS systems |
| gptkbp:is_part_of |
smart transportation systems
sustainable transportation initiatives smart city projects AI research initiatives future mobility solutions global transportation networks |
| gptkbp:is_promoted_by |
NVIDIA marketing campaigns
|
| gptkbp:is_promoted_through |
gptkb:educational_programs
social media campaigns partnerships with tech companies |
| gptkbp:is_supported_by |
gptkb:Documentation
gptkb:developers cloud computing resources data privacy regulations research funding community feedback open-source frameworks |
| gptkbp:is_tested_for |
performance metrics
real-world scenarios controlled environments simulation environments cybersecurity measures |
| gptkbp:is_used_for |
traffic management
|
| gptkbp:is_utilized_in |
public transportation systems
fleet management systems personal vehicles emergency response vehicles logistics and delivery services |
| gptkbp:provides |
real-time data processing
|
| gptkbp:reduces |
accident rates
|
| gptkbp:research |
academic institutions
|
| gptkbp:supports |
sensor fusion
V2 X communication |
| gptkbp:used_in |
autonomous driving systems
|
| gptkbp:uses |
GPU acceleration
|
| gptkbp:utilizes |
deep learning algorithms
|
| gptkbp:bfsParent |
gptkb:NVIDIA
|
| gptkbp:bfsLayer |
4
|