Editor’s note: This is the latest post in our NVIDIA DRIVE Labs series, which takes an engineering-focused look at… Read Article
DRIVE Labs
Most Popular
Read Between the Lines: How We Taught Neural Nets to Predict Lane Lines
Lane markings are critical guides for autonomous vehicles, providing vital context for where they are and where they’re going. That’s why detecting them with pixel-level precision is fundamentally important for… Read Article
To Go the Distance, We Built Systems That Could Better Perceive It
Simple rule: If you can’t judge distances you shouldn’t drive. The problem: judging distances is anything but simple. We humans, of course, have two high-resolution, highly synchronized visual sensors —… Read Article
DRIVE Labs: Predicting the Future with RNNs
Autonomous vehicles must use computational methods and sensor data, such as a sequence of images, to figure out how an object is moving in time…. Read Article
DRIVE Labs: Pursuing Perfection for Intersection Detection
Navigating a traffic-light controlled intersection may seem routine. But when the NVIDIA BB8 autonomous test vehicle first performed that task last year, it had our engineers smiling…. Read Article
DRIVE Labs: How We’re Building Path Perception for Autonomous Vehicles
Having confidence in a self-driving car’s ability to use data to perceive and choose the correct drivable path while the car is driving is critical. We call this path perception… Read Article