Four years ago, a system known as PilotNet became the first NVIDIA system to steer an autonomous car along a roadway. This system represents a departure from the classical approach for self-driving in which the process is manually decomposed into a series of modules, each performing a different task. In contrast, PilotNet is a single deep neural network (DNN) that takes pixels as input and…
]]>As part of our autonomous driving research, NVIDIA has created a deep-learning based system, known as PilotNet, which learns to emulate the behavior of human drivers and can be deployed as a self-driving car controller. PilotNet is trained using road images paired with the steering angles generated by a human driving a data-collection car. It derives the necessary domain knowledge from data.
]]>In a new automotive application, we have used convolutional neural networks (CNNs) to map the raw pixels from a front-facing camera to the steering commands for a self-driving car. This powerful end-to-end approach means that with minimum training data from humans, the system learns to steer, with or without lane markings, on both local roads and highways. The system can also operate in areas with…
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