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 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.

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.

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.

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.

A vehicle assistance system for a vehicle is provided. A corresponding computer implemented method and computer program product are also provided.

A vehicle assistance system for a vehicle is provided. A corresponding computer implemented method and computer program product are also provided.

Systems and methods are described for an adaptive user interface system for a vehicle with an automatic vehicle system. The adaptive user interface system includes a display and an electronic controller. The controller is configured to generate a graphical user interface indicative of operation of the automatic vehicle system, output the graphical user interface on the display, monitor an indicia of a driver's comfort level, and determine, based on the monitored indicia, when the driver is not comfortable with the operation of the automatic vehicle system. In response to determining that the driver is not comfortable with the operation of the automatic vehicle system, the electronic controller modifies the graphical user interface to provide an increased level of detail.

Systems and methods are described for an adaptive user interface system for a vehicle with an automatic vehicle system. The adaptive user interface system includes a display and an electronic controller. The controller is configured to generate a graphical user interface indicative of operation of the automatic vehicle system, output the graphical user interface on the display, monitor an indicia of a driver's comfort level, and determine, based on the monitored indicia, when the driver is not comfortable with the operation of the automatic vehicle system. In response to determining that the driver is not comfortable with the operation of the automatic vehicle system, the electronic controller modifies the graphical user interface to provide an increased level of detail.