Lateral control of an autonomous road vehicle in a simulated highway environment using adaptive resonance neural networks

Lateral control of a simulated vehicle in a simulated highway driving environment is explored. Three modules are used: a driving simulator, a visual preprocessor, and a neural network. Once trained, the networks control the trajectory of the vehicle by accessing a steering decision for implementation at each timestep in response to a visual encoding of an image generated at the previous timestep. The paper presents the development of the three system modules, the creation of training sets, and computational results. Neural network performances are gauged by a number of procedures. Excellent results are achieved for straight roads and curved roads under a variety of initial conditions on the vehicle