Acquisition of Vehicle Control Algorithms

摘要

In this paper, we present a multi-input multi-output (MIMO) data-acquired controller using system of hierarchical decision tables for a simulated vehicle driving control problem. The simulator incorporates dynamic mathematical model of a vehicle driving on a track. Sensor readings and expert driver control actions are accumulated to derive the vehicle control model. Sensor readings include random error to reflect realistic data acquisition conditions. The methodology of rough sets is being used to process the data and to automatically derive the control algorithm. In the experiments, the automated vehicle control algorithms derived from different driving patterns and with substantial sensor error consistently demonstrated astonishing robustness in their ability to properly drive the vehicle.