A transmission assembly includes a transmission assembly housing; a continuously variable power source (CVP) configured to generate CVP power; an input arrangement selectively coupled to receive the engine power from the input shaft and the CVP power from the CVP; a variator configured to receive the engine power and the CVP power through the input arrangement; and an output arrangement including an output shaft defining an output axis and at least one output component connected to the output shaft. A transmission gear arrangement is configured to provide a selective gear reduction for transmission of selected output power of the CVP power or combined power of the CVP power and the engine power. The transmission gear arrangement includes a plurality of range clutches supported about the output shaft and configured to be selectively engaged to transfer the selected output power from the variator shaft to the output shaft.

A framework for safely operating autonomous machinery, such as vehicles and other heavy equipment, in an in-field or off-road environment, includes detecting, identifying, and tracking objects from on-board sensors configured with the autonomous machinery as it performs activities in either an agricultural setting or a transportation environment. The framework generates commands for navigational control of autonomously-operated vehicles in response to detected objects and predicted tracks thereof for safe operation in the performance of those activities. The framework processes image data and range data in multiple fields of view around the autonomously-operated to discern and track objects in a deep learning to accurately interpret this data for determining and effecting such navigational control.

The present disclosure relates to systems and methods for host vehicle navigation. In one implementation, a navigation system for a host vehicle may include at least one processing device programmed to receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the plurality of images to identify a first flow of traffic and a second flow of traffic; determine a presence of at least one navigational state characteristic indicative of an alternating merging of the first flow of traffic and the second flow of traffic into a merged lane; cause at least a first navigational change to allow one target vehicle from the first flow of traffic to proceed ahead of the host vehicle; and cause at least a second navigational change to cause the host vehicle to follow the target vehicle into the merged lane.

A machine control system includes an agricultural work machine having an ECU coupled via a system bus to control engine functions, a GPS receiver, data collector, and specialized guidance system including a stored program. The data collector captures agricultural geospatial data including location data for the work machine and data from the ECU, and executes the stored program to: (a) capture geometries of the farm; (b) capture agricultural geospatial data; (c) automatically classify the agricultural geospatial data using the geometries of the farm, into activity/event categories including operational, travel, and ancillary events; (d) aggregate the classified data to create geospatial data events; (e) match the geospatial data events to a model to generate matched events; (f) use the matched events to generate actionable information for the working machine in real time or near real-time; and (g) send operational directives to the agricultural work machine based on the actionable information.

A method for operating an agricultural machine includes applying provided machine data of a work flow along a working route for an autonomous operation of the agricultural machine. The provided machine data includes a plurality of data sets. The method further includes recording, during the autonomous operation of the agricultural machine, a working position of the agricultural machine, and selecting and applying, as a function of the detected working position, a respective data set from the plurality of data sets of the provided machine data as a function of the detected working position.

The present disclosure relates to systems and methods for host vehicle navigation. In one implementation, a navigation system for a host vehicle may include at least one processing device programmed to receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the plurality of images to identify a first flow of traffic and a second flow of traffic; determine a presence of at least one navigational state characteristic indicative of an alternating merging of the first flow of traffic and the second flow of traffic into a merged lane; cause at least a first navigational change to allow one target vehicle from the first flow of traffic to proceed ahead of the host vehicle; and cause at least a second navigational change to cause the host vehicle to follow the target vehicle into the merged lane.

An agricultural vehicle monitoring system includes one or more noncontact sensors configured to sense multiple objects along a scanline. A comparative vehicle monitor is in communication with the one or more noncontact sensors. The comparative vehicle monitor is configured to provide a specified row width and to identify one or more crop rows from the scan line and determine one or more lengths of scan line segments between identified crop rows. The comparative vehicle monitor is further configured to determine a vehicle position including one or more of a vehicle angle or a vehicle location according to the specified row width and the one or more determined lengths of scan line segments between the identified crop rows.

A method and system for estimating surface roughness of a ground for an off-road vehicle to control steering of a vehicle, an implement, or both, comprises detecting motion data of an off-road vehicle traversing a field or work site during a sampling interval. A first sensor is adapted to detect pitch data of the off-road vehicle for the sampling interval to obtain a pitch acceleration. A second sensor is adapted to detect roll data of the off-road vehicle for the sampling interval to obtain a roll acceleration. An electronic data processor or surface roughness index module determines or estimates a surface roughness index based on the detected motion data, pitch data and roll data for the sampling interval. The surface roughness index can be displayed on the graphical display to a user or operator of the vehicle.

A method and system for estimating surface roughness of a ground for an off-road vehicle to control an implement comprises detecting motion data of an off-road vehicle traversing a field or work site during a sampling interval. A first sensor is adapted to detect pitch data of the off-road vehicle for the sampling interval to obtain a pitch acceleration. A second sensor is adapted to detect roll data of the off-road vehicle for the sampling interval to obtain a roll acceleration. An electronic data processor or surface roughness index module determines or estimates a surface roughness index based on the detected motion data, pitch data and roll data for the sampling interval. The surface roughness index can be displayed on the graphical display to a user or operator of the vehicle.

A method for controlling the speed of a work vehicle towing an implement that is movable between a working position, in which ground engaging tools of the implement are configured to perform a field operation, and a transport position, in which the ground engaging tools are raised relative to the ground. The method may include monitoring, with a computing device, an implement weight supported by the implement while the implement is in the transport position. The method may further include comparing, with the computing device, the implement weight to a predetermined threshold weight. Additionally, the method may include, when the implement weight differs from the predetermined threshold weight, adjusting, with the computing device, a maximum speed limit for the work vehicle.