A computer-implemented method for controlling a vehicle comprises: receiving tracking data associated with a surrounding environment of the vehicle; detecting, based upon the tracking data, an object in the surrounding environment of the vehicle; determining a location of the object; determining, based on navigation assistance data, whether the location of the object is at least partially within a classified area in the surrounding environment; and configuring a control system of the vehicle to: initiate, based upon determining that the location of the object is not at least partially within the classified area, a first collision avoidance response procedure for responding to the object; and initiate, based upon determining that the location of the object is at least partially within the classified area, a second collision avoidance response procedure for responding to the object, the second collision avoidance response procedure different from the first collision avoidance response procedure.

A system receives confirmation that a vehicle has accepted automatic control imposition for a drive within a geo-fenced boundary. The system tracks travel of a plurality of vehicles, including the vehicle, within the geo-fenced boundary. The system may determine that the vehicle has a threshold likelihood of encountering at least one of another vehicle or a boundary of the geo-fence at a threshold speed or above and responsive to the determination, impose automatic control on the vehicle, including at least one of controlled braking or speed limiting.

A system receives confirmation that a vehicle has accepted automatic control imposition for a drive within a geo-fenced boundary. The system tracks travel of a plurality of vehicles, including the vehicle, within the geo-fenced boundary. The system may determine that the vehicle has a threshold likelihood of encountering at least one of another vehicle or a boundary of the geo-fence at a threshold speed or above and responsive to the determination, impose automatic control on the vehicle, including at least one of controlled braking or speed limiting.

A product system for an agricultural sprayer includes a product tank configured to store a volume of an agricultural product. A fill station is configured to accept the agricultural product from an off-board source. A flow assembly is fluidly coupled with the fill station and is configured to direct the agricultural product into a product tank from the conduit. A reclaim system is configured to provide the agricultural product within the flow assembly to the product tank. A computing system is communicatively coupled to the reclaim system. The computing system is configured to receive inputs indicative of activation of a fill mode, detect termination of the fill mode, and activate a reclaim mode to move the agricultural product from at least the conduit to the product tank through activation of the reclaim system.

A product system for an agricultural sprayer includes a product tank configured to store a volume of an agricultural product. A fill station is configured to accept the agricultural product from an off-board source. A flow assembly is fluidly coupled with the fill station and is configured to direct the agricultural product into a product tank from the conduit. A reclaim system is configured to provide the agricultural product within the flow assembly to the product tank. A computing system is communicatively coupled to the reclaim system. The computing system is configured to receive inputs indicative of activation of a fill mode, detect termination of the fill mode, and activate a reclaim mode to move the agricultural product from at least the conduit to the product tank through activation of the reclaim system.

Control system and method which is adapted for use in a motor vehicle and intended to effect an at least semi-autonomous driving operation of the motor vehicle by means of assigned actuators on the basis of environmental data which are obtained from one or more environment sensors assigned to the motor vehicle, and wherein the control system is adapted and intended to detect a failure of a conventional steering system of the motor vehicle and attempt a change of direction of the vehicle, which corresponds to a desired steering angle, from current driving parameters by means of matched acceleration and/or deceleration interventions at individual wheel drives or wheel brakes, respectively, of the vehicle.

A braking force control system includes: a brake device and at least one electronic control unit. The brake device is configured to generate a braking force commensurate with a brake operation amount of a driver. At least one electronic control unit is configured to execute vehicle speed control for controlling a speed of a vehicle to a target speed by controlling a driving force and a braking force. The electronic control unit is configured to cause the brake device to generate an actual braking force corresponding to a total value of an additional braking force and an operational braking force when brake operation is performed during execution of the vehicle speed control. The additional braking force corresponds to a controlled braking force required by the vehicle speed control. The operational braking force is required through the brake operation.

In one embodiment, motion planning and control data is received, where the motion planning and control data indicates that an autonomous vehicle is to move from a first point to a second point of a path within a predetermined route. In response to the motion planning and control data, the path from the first point to the second point is segmented into multiple path segments. For each of the path segments, one of predetermined driving scenes is identified that matches motion characteristics of the corresponding path segment. The motion planning and control data associated with the path segments is modified based on predetermined motion settings of the path segments. The autonomous vehicle is driven through the path segments of the path based on the modified motion planning and control data.

In one embodiment, motion planning and control data is received, where the motion planning and control data indicates that an autonomous vehicle is to move from a first point to a second point of a path within a predetermined route. In response to the motion planning and control data, the path from the first point to the second point is segmented into multiple path segments. For each of the path segments, one of predetermined driving scenes is identified that matches motion characteristics of the corresponding path segment. The motion planning and control data associated with the path segments is modified based on predetermined motion settings of the path segments. The autonomous vehicle is driven through the path segments of the path based on the modified motion planning and control data.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.