Teaching Artificial Neural Systems To Drive: Manual Training Techniques For Autonomous Systems

J. F. Shepanski; S. A. Macy

doi:10.1117/12.942749

19 February 1988 Teaching Artificial Neural Systems To Drive: Manual Training Techniques For Autonomous Systems

J. F. Shepanski, S. A. Macy

Proceedings Volume 0848, Intelligent Robots and Computer Vision VI; (1988) https://doi.org/10.1117/12.942749
Event: Advances in Intelligent Robotics Systems, 1987, Cambridge, CA, United States

Abstract

We have developed a methodology for manually training autonomous control systems based on artificial neural systems (ANS). In applications where the rule set governing an expert's decisions is difficult to formulate, ANS can be used to extract rules by associating the information an expert receives with the actions he takes. Properly constructed networks imitate rules of behavior that permits them to function autonomously when they are trained on the spanning set of possible situations. This training can be provided manually, either under the direct supervision of a system trainer, or indirectly using a background mode where the network assimilates training data as the expert performs his day-to-day tasks. To demonstrate these methods we have trained an ANS network to drive a vehicle through simulated freeway traffic.

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J. F. Shepanski and S. A. Macy "Teaching Artificial Neural Systems To Drive: Manual Training Techniques For Autonomous Systems", Proc. SPIE 0848, Intelligent Robots and Computer Vision VI, (19 February 1988); https://doi.org/10.1117/12.942749

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