Adaptive Estimation of Information Values in Continuous Decision Making and Control of Remotely Piloted Vehicles
Annual technical rept.
PERCEPTRONICS INC WOODLAND HILLS CA
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This report describes research and development centered on evaluation of information needs in supervision of remotely piloted vehicles. The selection of information for transmission and display is a recurrent, subjective decision involving many factors - machine state, operator capabilities, communications costs, and channel limitations among others. An adaptive computer program has been developed which incorporates these factors into a multi-attribute decision model. The program is designed to capture the supervisory operators decision policy by using a training algorithm based on pattern recognition techniques. Preliminary tests of the adaptive modeling approach were made using a task simulation resembling control of a remotely piloted vehicle. Individual subjects navigated the RPV through a changing, hazardous environment. In doing so, the operators selected different combinations of information and control allocation. The adaptive model was found to be more predictive of the subjects behavior than either a constant, unity weight model or an off-line method of weight estimation. Also, prediction of behavior increased with presentation of model- based recommendations to the subjects. Finally, the model was found to be useful in identifying differing decision strategies. The multi-attribute model thus formulated is expected to find application in evaluation of alternative information needs. Methods for management of communications by the remote element are also discussed.
- Pilotless Aircraft
- Computer Programming and Software
- Human Factors Engineering and Man Machine Systems