Abstract
In this paper a neural-network automotive speed controller is presented which works at low and at high speed-levels using throttle and brake control input. It can be used for autonomous intelligent cruise control including stop-and-go traffic situations. The network itself consists of a simple multilayer feedforward perceptron network. A special training method is used, where the neural network is trained on a detailed nonlinear dynamic vehicle model. Practical road tests with the Daimler Benz experimental vehicle OSCAR (MB 300 TE station wagon) show good results for both high- and low-speed control.
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