Abstract: A policy map is obtained that includes a first set of machine settings values for controlling a machine to perform an operation at a site, at different locations in the field. An adjustment component receives sensor signals indicating conditions that will be encountered by the machine in the future, as it moves through the site. A cost determination component determines whether an adjustment is to be made to the first set of settings values, based upon the sensor signals. A predictive vehicle model provides an expected vehicle response, based upon the adjusted settings values that are selected. Control signals are generated based upon adjusted setting values that are generated from the policy map, the expected vehicle response, and the future condition sensor signals. The control signal generator generates the control signals to control a set of controllable subsystems.

Abstract: A policy map is obtained that includes a first set of machine settings values for controlling a machine to perform an operation at a site, at different locations in the field. An adjustment component receives sensor signals indicating conditions that will be encountered by the machine in the future, as it moves through the site. A cost determination component determines whether an adjustment is to be made to the first set of settings values, based upon the sensor signals. A predictive vehicle model provides an expected vehicle response, based upon the adjusted settings values that are selected. Control signals are generated based upon adjusted setting values that are generated from the policy map, the expected vehicle response, and the future condition sensor signals. The control signal generator generates the control signals to control a set of controllable subsystems.