Abstract: A vehicle capable of operating autonomously, a system for generating a notification for a behavior of the vehicle includes a method of generating the notification using artificial intelligence. The system includes an interface and a processor. The processor is configured to determine a current state of the vehicle, determine probabilities for a plurality of trajectories through a behavior model of the vehicle, each trajectory indicating one or more decisions from the current state to a subsequent state of the vehicle using the behavior model for the vehicle, generate a message to be presented as the vehicle performs the behavior that is determined by the artificial intelligence system, wherein the behavior is selected based on the probabilities, determine a temporal parameter for the message, determine a modality parameter for the message, and present the message at the interface using the temporal parameter and the modality parameter.

Abstract: A system and method for limited rate context-based eye gaze encoding includes generating, based on an outward looking camera situated in a vehicle, a first video stream of a surrounding environment to a controller. The controller generates a scene description based on the first video stream and selects a corresponding scene from a predefined list of known scenes. Further, the controller, based on the selected corresponding scene, selects a codebook of encoding and decoding parameters from a plurality of predefined codebooks. Based on an inward looking camera situated in the vehicle, a second video stream of a face of a driver to an eye tracker controller is generated, where the eye tracker controller estimates a gaze direction of the driver. Encoded data comprising the estimated gaze direction of the driver is transmitted over a bandwidth limited channel to a decoder, based on the selected codebook, the encoded data.

Abstract: An autonomous vehicle and a system a method of operating a machine. The system includes a processor. A set of explanations related to a machine behavior of the machine is generated. The processor generates a model that relates an explanation for the behavior taken in response to a scenario to a trust level that a human has in the behavior when the explanation is presented to the human, the explanation being selected from the set of explanations. The processor performs the behavior of the system of vehicle in response to the scenario, uses the model to select the explanation when the behavior is taken, and presents the explanation to the human.

Abstract: A vehicle communication and control system includes a first vehicle in signal communication with a remote computing system and/or a second vehicle. The first vehicle includes a sensor configured to capture a raw image having a first image volume and including at least one target object. An image encoder included in the vehicle converts the raw image into a masked image having a second image volume that is less than the first image volume. A segmentation unit included in the remote computing system and/or the second vehicle determines the at least one target object from the masked image, generates a masked segmented image including a sparse segmentation of the at least one target object, and converts the sparse segmentation of the at least one target object into at least one recovered segmented target object indicative of the at least one target object.

Abstract: A vehicle includes a system method of operating the vehicle. The system includes a processor. The processor is configured to determine a machine-selected action for the vehicle in a current state and an actual next state for the vehicle resulting from the machine-selected action, determine, using a user model, a user-expected action for the vehicle in the first current state and a user-expected next state for the vehicle resulting from applying the machine-selected action, determine a gap value based on at least one of the user-expected action, the machine-selected action, the actual next state and the user-expected next state, and output a signal when the gap value meets a threshold.

Abstract: A system for control of an automated device includes a control system configured to operate a device during an operating mode corresponding to a first state in which the control system automatically controls operation, the operating mode prescribing that a user monitor the device operation during automated control, and a scheduling module configured to, during the operating mode, receive a request for the user to temporarily stop monitoring in order to perform a task unrelated to the device operation, allocate a time period during which automated control is maintained and the user stops monitoring, the time period including a non-monitoring period having a duration based on a minimum amount of time for the task, and put the device into a temporary state at initiation of the allocated time period during which the user stops monitoring and automated control is maintained.

Abstract: A system for user interaction with an automated device includes a control system configured to operate the device during an operating mode corresponding to a first state in which the control system automatically controls the device operation, and the operating mode prescribes that a user monitor the device operation during automated control. The control system is configured to allocate a time period for the device to transition to a temporary state in which automated control is maintained and the user is permitted to stop monitoring and perform a task unrelated to device operation. The system includes a user interaction system including a visual display configured to present trajectory information, an indication as to whether an area is conducive to putting the device in the temporary state, and time period allocation information, the user interaction system including an interface engageable by the user to manage scheduling of allocated time period(s).

Abstract: A method in a rate adaptive system includes categorizing, by an encoder, a plurality of clusters of data in a segmented image into one of a plurality of categories corresponding to a different predetermined label with a predetermined priority level; vectorizing, by the encoder, the data to generate a sparse vector xi for its corresponding label; encoding, by the encoder, a plurality of the sparse vectors xi by multiplying a measurement matrix Ai(t) with the sparse vector xi to generate a set of encoded information yi; transmitting, by the encoder to the decoder, the plurality of sets of the encoded information yi in a prioritized order; decoding, by the decoder, the plurality of sets of encoded information yi to determine the plurality of the sparse vectors xi based on determining measurement matrix Ai(t); and uniting the plurality of the sparse vectors xi into a single image frame.

Abstract: A vehicle communication and control system includes a first vehicle in signal communication with a remote computing system and/or a second vehicle. The first vehicle includes a sensor configured to capture a raw image having a first image volume and including at least one target object. An image encoder included in the vehicle converts the raw image into a masked image having a second image volume that is less than the first image volume. A segmentation unit included in the remote computing system and/or the second vehicle determines the at least one target object from the masked image, generates a masked segmented image including a sparse segmentation of the at least one target object, and converts the sparse segmentation of the at least one target object into at least one recovered segmented target object indicative of the at least one target object.

Abstract: A method in a rate adaptive system includes categorizing, by an encoder, a plurality of clusters of data in a segmented image into one of a plurality of categories corresponding to a different predetermined label with a predetermined priority level; vectorizing, by the encoder, the data to generate a sparse vector xi for its corresponding label; encoding, by the encoder, a plurality of the sparse vectors xi by multiplying a measurement matrix Ai(t) with the sparse vector xi to generate a set of encoded information yi; transmitting, by the encoder to the decoder, the plurality of sets of the encoded information yi in a prioritized order; decoding, by the decoder, the plurality of sets of encoded information yi to determine the plurality of the sparse vectors xi based on determining measurement matrix Ai(t); and uniting the plurality of the sparse vectors xi into a single image frame.

Abstract: A method of near-lossless universal data compression using correlated data sequences includes detecting first target surroundings via a first sensor, encoding a first data sequence indicative of the detected target surroundings, and communicating to an electronic controller, the encoded first data sequence. The method additionally includes detecting the first target surroundings via a second sensor, and encoding a second data sequence indicative of the target surroundings detected by the second sensor. The method also includes communicating the encoded second data sequence to the controller. The method additionally includes decoding, via the controller, the encoded first and second data sequences. The method also includes, via the controller, determining a statistical correlation between the decoded first and second data sequences and formulating a mapping function having reduced cardinality and indicative of the determined statistical correlation.

Abstract: A method of data sequence processing assisted by an information technology (IT) cloud platform includes detecting target surroundings, via a first sensor arranged on a first vehicle traversing the target surroundings. The method also includes communicating, to the IT cloud platform via a first electronic controller arranged on the first vehicle, a processed first data set indicative of a characteristic of the detected target surroundings. The method additionally includes merging, on the IT cloud platform, the processed first data set with an IT cloud data set residing on the IT cloud platform to generate a combined data set indicative of the characteristic of the target surroundings. A data sequence processing system assisted by the IT cloud platform is also disclosed.

Abstract: A method is provided for designing an integrated circuit. The method includes inserting wire model objects into the schematic of said circuit based on sizing and placement of components of the circuit, and performing an early timing analysis on said schematic. The steps of inserting and performing are repeated after re-sizing and/or re-placing the components if early timing analysis fails.

Abstract: The present invention is a method and system for modeling wiring routing in circuit design. According to some embodiments, the wire model objects (“WMO”) may be inserted into the wiring routing on a ‘WMO-per-segment’ basis. According to some other embodiments, the wire model objects may be inserted into the wiring routing per groups of sequential segments. The entire wiring routing geometry may constitutes one group, and a wire model object may be inserted between the source point(s) and the target points based on the longest path in the routing geometry. An insertion rule may be selected based on any combination of the following factors: segment length, total path length, spacing between adjacent segments, wire metal and wire width. A wire model object may be selected from a group consisting of: {“C”; one “RC” arrangement; ‘n’ times “?”-type filter arrangement, wherein n=1, 2, 3, . . . , }.

Abstract: The present invention is a method and system for schematically embedding wire model objects into a schematic design of an integrated circuit. The method includes estimating a wiring routing geometry for each signal path in the circuit, selecting one or more cascading wire model objects (“WMOs”) for each segment in each geometry, and substituting each signal path with the respective one or more WMOs.

Abstract: The present invention is a method and system for schematically embedding wire model objects into a schematic design of an integrated circuit. The method includes estimating a wiring routing geometry for each signal path in the circuit, selecting one or more cascading wire model objects (“WMOs”) for each segment in each geometry, and substituting each signal path with the respective one or more WMOs.

Abstract: A method is provided for designing an integrated circuit. The method includes inserting wire model objects into the schematic of said circuit based on sizing and placement of components of the circuit, and performing an early timing analysis on said schematic. The steps of inserting and performing are repeated after re-sizing and/or re-placing the components if early timing analysis fails.

Abstract: The present invention is a method and system for modeling wiring routing in circuit design. According to some embodiments, the wire model objects (“WMO”) may be inserted into the wiring routing on a ‘WMO-per-segment’ basis. According to some other embodiments, the wire model objects may be inserted into the wiring routing per groups of sequential segments. The entire wiring routing geometry may constitutes one group, and a wire model object may be inserted between the source point(s) and the target points based on the longest path in the routing geometry. An insertion rule may be selected based on any combination of the following factors: segment length, total path length, spacing between adjacent segments, wire metal and wire width. A wire model object may be selected from a group consisting of: {“C”; one “RC” arrangement; ‘n’ times “?”-type filter arrangement, wherein n=1, 2, 3, . . . , }.