- The Autonomous Land Vehicle In a Neural Network (ALVINN) is a perception system which learns to control the NAVLAB vehicles by watching a person drive
- One of the first examples that neural-networks could do "real-work". It can drive 70mph on highways.
- ALVINN's architecture consists of a single hidden layer back-propagation network.
- The input layer of the network is a 30x32 unit two dimensional "retina" which receives input from the vehicles video camera.
- Each input unit is fully connected to a layer of five hidden units which are in turn fully connected to a layer of 30 output units. The output layer is a linear representation of the direction the vehicle should travel in order to keep the vehicle on the road.