Abstract: A method for autonomously controlling a vehicle includes establishing decision variables for maneuvering the vehicle. Behavior functions are established for behaviors of the vehicle as a function of at least one of the established decision variables. These behavior function give a score which may be weighted, indicating the desirability of engaging in the associated behavior. A summation of the weighted behavior functions can be solved while the vehicle is operating to determine the values of the decision variables giving the highest summation of scores. In a preferred method, an optimal structure for the behavior functions and summation solution is taught. The method then guides the vehicle in accordance with the determined decision variable values.

Abstract: A mathematical programming method in which a common decision space is defined by identifying decision variables, and a set of objective functions is developed as piecewise defined functions. Each objective function is dependent on at least one of the decision variables and corresponds to a goal. The objective function has a plurality of pieces, such that the objective function has only one piece for each combination of decision variables. A value function is developed in additive preference form based on weights and the objective functions. The value function is optimized by searching through the decision variable values to find the values of the decision variables that maximize the developed value function. An action dictated by the decision variable values can then be executed.