A method may include obtaining input information relating to an environment in which an autonomous vehicle (AV) operates, the input information describing at least one of: a state of the AV, an operation of the AV within the environment, a property of the environment, or an object included in the environment. The method may include identifying a first object in the vicinity of the AV based on the obtained input information. The method may include determining a first object rule corresponding to the first object, the first object rule indicating suggested driving behavior for interacting with the first object. The method may include determining a first decision that follows the first object rule and sending an instruction to a control system of the AV, the instruction describing a given operation of the AV responsive to the first object rule according to the first decision.

An information processing apparatus receives a completion notification that indicates the completion of updating of first software that controls the display on a first monitor provided in an autonomous vehicle. Then, the information processing apparatus updates, triggered by the reception of the completion notification, second software that controls the display on a second monitor used for remotely monitoring the operation of the autonomous vehicle.

An information processing apparatus receives a completion notification that indicates the completion of updating of first software that controls the display on a first monitor provided in an autonomous vehicle. Then, the information processing apparatus updates, triggered by the reception of the completion notification, second software that controls the display on a second monitor used for remotely monitoring the operation of the autonomous vehicle.

The routing apparatus predicts occurrence of remote assistance for each vehicle based on a currently selected route of each vehicle and an operation status of each vehicle and predicts an operating rate of operators as a whole based on a prediction result of the occurrence of remote assistance for each vehicle. When the operating rate is higher than the target range, the routing apparatus changes the combination of routes of all vehicles being remotely monitored to a combination that reduces an assistance cost of the operators as a whole as compared with a currently selected combination. When the operating rate is lower than the target range, the routing apparatus changes the combination of routes of all vehicles being remotely monitored to a combination that reduces a vehicle cost of vehicles as a whole as compared with the currently selected combination.

The subject matter of this specification can be implemented in, among other things, a system that includes a first light source to produce a pulsed beam and a second light source to produce a continuous beam, a modulator to impart a modulation to the second beam, and an optical interface subsystem to transmit the pulsed beam and the continuous beam to an outside environment and to detect a plurality of signals reflected from the outside environment. The system further includes one or more circuits configured to identify associations of various reflected pulsed signals, used to detect distance to various objects in the environment, with correct reflected continuous signals, used to detect velocities of the objects. The one or more circuits identify the associations based on the modulation of the detected continuous signals.

An agricultural system includes a target vehicle configured to harvest crops and a work vehicle. The work vehicle includes a controller. The controller includes a memory and a processor, and the controller is configured to receive or determine a plurality of vehicle paths as well as a location of the target vehicle. The controller is also configured to identify an active path of the plurality of vehicle paths based on the location of the target vehicle. The target path is a path traversed by the target vehicle.

The present invention discloses a system for detecting an obstacle for a vehicle. The system includes an information collection unit that monitors movement information of a vehicle, road information, and location information of the vehicle; a determination unit that determines whether the vehicle enters a special mode in which the vehicle turns and moves backward on a road through the movement information of the vehicle, the road information, and the location information of the vehicle from the information collection unit; and a controller that deactivates a rear monitoring function of either side of the vehicle in response to a determination that the vehicle enters the special mode.

Trajectory generation for controlling motion or other behavior of an autonomous vehicle may include alternately determining a candidate action and predicting a future state based on that candidate action. The technique may include determining a cost associated with the candidate action that may include an estimation of a transition cost from a current or former state to a next state of the vehicle. This cost estimate may be a lower bound cost or an upper bound cost and the tree search may alternately apply the lower bound cost or upper bound cost exclusively or according to a ratio or changing ratio. The prediction of the future state may be based at least in part on a machine-learned model's classification of a dynamic object as being a reactive object or a passive object, which may change how the dynamic object is modeled for the prediction.

A robot assembly for safe operation in a manufacturing setting with humans including a sensor for detecting a human location and human movement is provided. A safety control module providing a boundary of a safety zone area that is associated with the human in a task oriented state that includes a largest possible area in which the human or an associated work object can extend when the human is standing in one location and performing the work task. The human movement and safety zone area location being used to develop a capture set area that includes at least one predictive future safety zone area location. Using the at least one predicted future safety zone area, establishing a travel path for moving the robot between locations without overlapping the capture set area.

A pedestrian tracking system includes: a buffer or a memory configured to store a trajectory sequence of a pedestrian; a step attention module and a control module. The step attention module iteratively performs a step attention process to predict states of the pedestrian. Each iteration of the step attention process includes the step attention module: learning the stored trajectory sequence to provide time-dependent hidden states, reshaping each of the time-dependent hidden states to provide two-dimensional tensors; condensing the two-dimensional tensors via convolutional networks to provide convolutional sequences; capturing global information of the convolutional sequences to output a set of trajectory patterns represented by a new sequence of tensors; learning time-related patterns in the new sequence and decoding the new sequence to provide one or more of the states of the pedestrian; and modifying the stored trajectory sequence to include the predicted one or more of the states of the pedestrian.