The present disclosure provides a method including determining an operational mode of a vehicle based on data accumulated from at least one vehicle information system associated with the vehicle; selecting one of a plurality of power consumption profiles for the vehicle based on the determined operational mode; and applying the selected one of the power consumption profiles to the vehicle.

An autonomous driving controller includes a plurality of parallel processors operating on common input data. Each of the plurality of parallel processors includes a general processor, a security processor subsystem (SCS), and a safety subsystem (SMS). The general processors, the SCSs, and the SMSs of the plurality of parallel processors are configured to first, boot the plurality of SCSs from ROM second, boot the plurality of SMSs of the plurality of parallel processors from RAM or ROM, and, third, boot the plurality of general processors of the plurality of parallel processors from RAM. Between booting of the SCSs and the SMSs, at least one of the plurality of SCSs may load SMS boot code into the RAM that is dedicated to the plurality of SMSs.

An on-board computing system for a vehicle is configured to generate and selectively present a set of autonomous-switching directions within a navigation user interface for the operator of the vehicle. The autonomous-switching directions can inform the operator regarding changes to the vehicle's mode of autonomous operation. The on-board computing system can generate the set of autonomy-switching directions based on the vehicle's route and other information associated with the route, such as autonomous operation permissions (AOPs) for route segments that comprise the route. The on-board computing device can selectively present the autonomy-switching directions based on locations associated with anticipated changes in autonomous operations determined for the route of the vehicle, the vehicle's location, and the vehicle's speed. In addition, the on-board computing device is further configured to present audio alerts associated with the autonomy-switching directions to the operator of the vehicle.

An occlusion detection system for an autonomous vehicle is described herein, where a signal conversion system receives a three-dimensional sensor signal from a sensor system and projects the three-dimensional sensor signal into a two-dimensional range image having a plurality of pixel values that include distance information to objects captured in the range image. A localization system detects a first object in the range image, such as a traffic light, having first distance information and a second object in the range image, such as a foreground object, having second distance information. An occlusion polygon is defined around the second object and the range image is provided to an object perception system that excludes information within the occlusion polygon to determine a configuration of the first object. A directive is output by the object perception system to control the autonomous vehicle based upon occlusion detection.

A helicopter autopilot system includes an inner loop for attitude hold for the flight of the helicopter including a given level of redundancy applied to the inner loop. An outer loop is configured for providing a navigation function with respect to the flight of the helicopter including a different level of redundancy than the inner loop. An actuator provides a braking force on a linkage that serves to stabilize the flight of the helicopter during a power failure. The actuator is electromechanical and receives electrical drive signals to provide automatic flight control of the helicopter without requiring a hydraulic assistance system in the helicopter. The autopilot can operate the helicopter in a failed mode of the hydraulic assistance system. A number of flight modes are described with associated sensor inputs including rate based and true attitude modes.

The present teaching relates to method, system, and medium, for generating an augmented alert in a hybrid vehicle. First information indicating an upcoming switch in an operating mode of the vehicle is received, which specifies a set of tasks, arranged in an order, to be completed by a driver in the vehicle to achieve the upcoming switch, and a task duration for each of the set of tasks by which the task is to be completed. A current state of the driver is obtained and used to determine a set of warnings to alert the driver to perform the set of tasks. Each warning corresponds to a task in the set of tasks and is created based on the current state of the driver. A warning schedule is generated based on the set of warnings in the order of the set of tasks and transmitted so that warnings in the warning schedule are delivered to the driver.

Operating conditions corresponding to a harvesting operation being performed by a mobile harvesting machine are detected along with a priority of a first performance pillar metric relative to a second performance pillar metric. An operating characteristic of the mobile harvesting machine is detected and a performance pillar metric value is identified for the first performance pillar metric based on the detected operating characteristic. A performance limitation corresponding to the first performance pillar metric is identified based on the detected operating conditions and an aggressiveness setting is detected that is indicative of an operating settings change threshold. It is then determined whether a settings change is to be performed based on the first performance pillar metric value, the priority of the first performance pillar metric, the first performance limitation and the settings change threshold and if the settings change is to be performed, a settings change actuator is controlled to execute the settings change.

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

An autonomous vehicle safety system may activate to prevent collisions by detecting that a planned trajectory may result in a collision. If the safety system is overly sensitive, it may cause false positive activations, and if the system isn't sensitive enough the collision avoidance system may not activate and prevent a collision, which is unacceptable. It may be impossible or prohibitively difficult to detect false positive activations of a safety system and it is unacceptable to risk a false negative, so tuning the safety system is notoriously difficult. Tuning the safety system may include detecting near-miss events using surrogate metrics, and tuning the safety system to increase or decrease a rate of near-miss events as a stand-in for false positives.

Aspects described herein include an autonomous surface vehicle (ASV) for operation within an inventory system of an environment. The ASV includes a drive system, a docking system, a plurality of sensors, and a memory storing a map of the environment. The ASV further includes one or more computer processors configured to (i) detect, using a location sensor, a location of the ASV within the environment; (ii) control the drive system to actuate the ASV toward a corridor defined in the map at a first speed setting; and control the drive system to actuate the ASV through the corridor along at least one barrier defined in the map. A second, greater speed setting is applied when (i) the location sensor indicates that the ASV is within the corridor and (ii) one or more fiducials along the at least one barrier are visually detected by one or more proximity sensors.