A light system associated with an agricultural machine may include a sensor configured to sense a fill level in a storage container, a first light source configured to be selectively operated, one or more processors, and a non-transitory computer-readable storage medium coupled to the one or more processors and storing programming instructions for execution by the one or more processors. The programming instructions may instruct the one or more processors to determine the fill level of the storage container based on a sensor output of the sensor and operate the first light source according to a light parameter program based on the determined fill level. The first light source may be operated according to different light parameter programs for different fill levels.

An estimation and control system generates a metric indicative of whether a combine harvester can perform a headland pass to open a field, without needing to be unloaded. If the metric indicated that the combine harvester will likely need to be unloaded, the estimation and control system determines whether the field can be partitioned into smaller tracts so that the combine harvester can perform a breakthrough pass on a smaller tract without needing to be unloaded. A control signal is generated based upon whether the combine harvester can perform a pass without needing to be unloaded.

One or more information maps are obtained by an agricultural system. The one or more information maps map one or more characteristic values at different geographic locations in a worksite. An in-situ sensor detects a material dynamics characteristic value as a mobile machine operates at the worksite. A predictive map generator generates a predictive map that predicts a predictive material dynamics characteristic value at different geographic locations in the worksite based on a relationship between the values in the one or more information maps and the material dynamics characteristic value detected by the in-situ sensor. The predictive map can be output and used in automated machine control.

A computer implemented method includes obtaining historical operation data relative to a plurality of historical operations, the historical operation data including historical machine data, historical worksite data, historical productivity data, and historical logistics data; obtaining current operation data relative to an underway or upcoming operation, the current operation data including current machine data and current worksite data; generating, based on the obtained historical operation data and the obtained current operation data, an operation plan output relative to the underway or upcoming operation, the operation plan output including one or more of: (i) one or more machine routes; (ii) one or more sub-operation locations; (iii) one or more operation plan maps; or a combination of (i), (ii), and (iii); and generating control signals to control one or more mobile agricultural work machines based on the operation plan output.

A first in-situ sensor detects a characteristic value as a mobile machine operates at a worksite. A second in-situ sensor detects a material dynamics characteristic value as the mobile machine operates at the worksite. A predictive model generator generates a predictive model that models a relationship between the characteristic and the materials dynamics characteristic based on the characteristic value detected by the first in-situ sensor and the material dynamics characteristic value detected by the second in-situ sensor. The predictive model can be output and used in automated machine control.

An automation system is configured to automatically adjust an operational setting of an agricultural vehicle while performing an operation in a field in order to adjust an operational output parameter of the agricultural vehicle. A method of training the automation system comprises receiving operational information including at least a location of the agricultural vehicle and georeferenced field information. The method further comprises, based on the location of the agricultural vehicle and the georeferenced field information, deciding to run a training sequence. The training sequence comprises measuring the operational output parameter, changing the operational setting, monitoring a subsequent change of the operational output parameter, and updating the automation system based on the changing of the operational setting and the subsequent change of the operational parameter.

Computer aided design (CAD) files for a plurality of different kinds of receiving vehicles are loaded to a remote server. Based on a receiving vehicle identifier, a corresponding CAD file or information derived from a CAD file is sent to a leading vehicle that is performing an unloading operation to load material into the receiving vehicle. An unloading control system controls the unloading operation based on the CAD file or information.