Abstract: Aspects of the disclosure relate to evaluating quality of a predetermined pullover location for an autonomous vehicle. For instance, a plurality of inputs for the predetermined pullover location may be received. The plurality of inputs may each include a value representative of a characteristic of the predetermined pullover location. The plurality of inputs may be combined to determine a pullover quality value for the predetermined pullover location. The pullover quality value may be provided to a vehicle in order to enable the vehicle to select a pullover location for the vehicle.

Abstract: Accurate operation of a current monitor is provided by injecting a bias voltage to a maintain de-selected sense amplifier input in an active state. An electronic system includes an output stage to supply a load current and includes two push-pull output drivers having sense resistors supplying a first and a second sense voltage. An included mode control circuit selects between a first and a second operating mode and selects a polarity of the current. An included current monitor receives the sense voltages and has a control input coupled to the mode selection control circuit. The current monitor provides an output that is dependent on both sense voltages in the first operating mode and is indicative of one of the sense voltages selected according to the selected polarity in the second operating mode. The bias voltage is injected into an unselected sense inputs to maintain active operation of the sense amplifier.

Abstract: Aspects of the disclosure relate to evaluating quality of a predetermined pullover location for an autonomous vehicle. For instance, a plurality of inputs for the predetermined pullover location may be received. The plurality of inputs may each include a value representative of a characteristic of the predetermined pullover location. The plurality of inputs may be combined to determine a pullover quality value for the predetermined pullover location. The pullover quality value may be provided to a vehicle in order to enable the vehicle to select a pullover location for the vehicle.

Abstract: A buffer in an integrated circuit comprises one or more logic circuits, an input signal pin electrically coupled to an input of one of the one or more logic circuits, and an output signal pin electrically coupled to an output of one of the one or more logic circuits. The input signal pin and output signal pin are positioned on a same routing track of the integrated circuit which specifies a routing in the integrated circuit. A respective segment of a net routed to the input and output signal pin is on the same routing track.

Abstract: A damage assessment method is provided. The method comprises recognizing a region of interest in an image that corresponds to a visible damage inflicted on a target object. The method further comprises determining a first plurality of feature values for a plurality of image features based on the recognized region of interest. The method further comprises retrieving, from a memory, time-series information that indicates a usage pattern of the target object and determining a second plurality of feature values for a plurality of usage features based on the retrieved time-series information. The method further comprises providing the first plurality of feature values and the second plurality of feature values as input to a trained classifier and predicting a true age of the visible damage based on a classification output of the trained classifier for the first plurality of feature values and the second plurality of feature values.

Abstract: A method for predictive maintenance of a component of a vehicle includes collection of first operational data, from a telematics device of the vehicle, for a set of parameters associated with the component. From the first operation data, a first dataset is selected based on an engine status of an engine of the vehicle. The first dataset is processed to obtain a plurality of feature values and the plurality of feature values are segregated into a plurality of clusters. A classifier is trained based on the plurality of clusters to determine the health status of the component. Real-time or near real-time operational data for the set of parameters is received, from the telematics device of the vehicle. The received operational data is used as an input to the trained classifier and the health status of the component is determined based on an output of the trained classifier.

Abstract: A method for facilitating vehicle servicing is provided. A first plurality of feature values corresponding to a first plurality of features are determined, for each of a plurality of vehicles. A second plurality of feature values corresponding to a second plurality of features are determined, for each of a plurality of service centers at which the plurality of vehicles were serviced. Based on the first and second pluralities of feature values, a machine learning model is trained to predict service completion times for servicing vehicles. For determining a service completion time for servicing a first vehicle at a first service center, a vehicular dataset of the first vehicle is provided as input to the machine learning model. The machine learning model predicts the service completion time based on the inputted vehicular dataset. The first vehicle is serviced at the first service center in compliance with the predicted service completion time.

Abstract: Generation of an autonomy map for assisting an autonomous vehicle includes extracting the historical autonomy information associated one or more route segments of one or more routes. An autonomy level for each route segment is determined based on the extracted historical autonomy information. A digital autonomy map is generated including each route segment of at least one route such that each route segment is tagged with the determined autonomy level. The autonomy level of each route segment is dynamically updated in real-time for providing real-time driving assistance to the autonomous vehicle.

Abstract: A system may include a pulse-width modulation mode path configured to drive a load at an output of the system in a first mode of operation, a linear mode path configured to drive the load in a second mode of operation, a common mode control feedback loop configured to set a value of a common mode output signal at the output in the second mode of operation, and an auxiliary circuit coupled to the common mode feedback control loop and configured to maintain a state of the common mode feedback control loop during the first mode of operation as the state was or will be during the second mode of operation.

Abstract: A method for asset health management is provided. The method includes receiving, first maintenance data, first booking data, first vehicle data, first operational data, and a labelled dataset for a set of vehicles over a first time-interval. The labelled dataset includes at least an actual health index for each vehicle observed over the first time-interval. The method includes determining a first plurality of features and a corresponding first plurality of feature values based on the first maintenance data, the first booking data, the first vehicle data, and the first operational data. The method includes training a prediction model based on the first plurality of features, the first plurality of feature values, and the labelled dataset. The method includes determining a health index of a target vehicle based on the trained first prediction model and a first dataset associated with the target vehicle.

Abstract: Aspects of the technology provide a method including receiving a request for a user to be picked up or dropped off by an autonomous vehicle, in which the request identifying a location, and determining a land parcel containing the identified location. The method also includes identifying a set of features that are within a selected distance from the identified location, filtering the set of identified features to obtain only curated features that are within the selected distance from the identified location, determining a distance between each curated feature and the identified location, and inferring an access point for the identified location based on the distances determined between each curated feature and the identified location. The inferred access point can then be provided to enable the autonomous vehicle to perform a pickup or drop-off.

Abstract: Systems and methods include operating a label distribution protocol (LDP) session with a peer node in a network; responsive to a change in graceful restart of the LDP session, sending a notification message to the peer node with a graceful restart capability change indication; responsive to receiving a second notification message from the peer node with graceful restart capability change indication, updating the graceful restart capability for the LDP session; and, responsive to failing to receive the second notification message, leaving the graceful restart capability as it was prior to the change.

Abstract: An example method includes setting an initial pickup location. The method includes causing an autonomous vehicle to navigate towards the initial pickup location. The method includes periodically generating a plurality of candidate updated pickup locations. The method includes selecting a suggested pickup location from the plurality of candidate pickup locations that achieves a benchmark for reducing one or more of a time and a distance associated with the initial pickup location for one or more of the autonomous vehicle and the client device. The method includes determining that the suggested pickup location satisfies a set of pre-update checks for limiting a number of pickup location updates. The method includes responsive to (i) selecting the suggested pickup location, and (ii) determining that the suggested pickup location satisfies the set of pre-update checks, causing the autonomous vehicle to navigate to the suggested pickup location.

Abstract: A method for determining a driver score for a first driver of a first vehicle. The method comprises receiving, from a database server, first maintenance data, first booking data, and first vehicle data associated with a plurality of vehicles, and first driver behavioral data for a plurality of drivers. The method includes obtaining a plurality of features and a plurality of feature values based on the first maintenance data, the first booking data, the first vehicle data, and the first driver behavioral data. The method further includes segregating the plurality of feature values into a plurality of clusters. The method includes training a classifier to determine the driver score. The method further includes receiving from the database server, a first dataset associated with the first vehicle and the first driver. The method includes determining the driver score for the first driver based on an output of the trained classifier.

Abstract: A method for vehicle maintenance at a service center is provided. A set of vehicular datasets for a set of vehicles, at a service center, is retrieved from a database. Based on the set of vehicular datasets, a service schedule for servicing the set of vehicles is determined. The service schedule is indicative of a first sequence for servicing the set of vehicles. The servicing of a first subset of the set of vehicles is initiated based on the first sequence. A progress of the servicing of the first subset of the set of vehicles is monitored based on status reports. Based on the monitored progress, the service schedule for a second subset of the set of vehicles is updated. Based on the updated service schedule, the servicing of the second subset of the set of vehicles is initiated based on a second sequence.

Abstract: Methods, systems, and computer readable media for selecting a software defined wide area network (SD-WAN) link using network slice information are disclosed. One method occurs at an SD-WAN controller implemented using at least one processor, the method comprises: receiving a packet containing packet header information including at least one internet protocol (IP) address; determining, using the packet header information, a link selection rule for selecting an SD-WAN link for transmission, wherein the link selection rule uses transmission characteristics associated with the packet, wherein the transmission characteristics are discerned using network slice information associated with the packet; selecting, using the link selection rule, the SD-WAN link; and transmitting the packet via the SD-WAN link.

Abstract: The present invention relates to a kit comprising: at least one microneedle sheet (1) comprising a substrate layer and a plurality of microneedles on the substrate layer, the microneedles comprising at least one water-soluble or water-dispersible polymer; and a device comprising an applicator (2-3) comprising an application surface, a container (2-1) comprising a cosmetic composition and a valve, wherein the microneedle sheet (1) is capable being attached to the applicator (2-3) by attaching the substrate layer of the microneedle sheet to the application surface, the applicator (2-3), the container (2-1) and the valve are configured to supply the cosmetic composition via the valve onto the microneedle sheet (1). The kit according to the present invention can prevent the repeated use of microneedles (1), and can apply a cosmetic product in an easy and sanitary manner.

Abstract: A Point of Local Repair (PLR) network element includes one or more ports and circuitry connected thereto for forwarding and control, wherein the circuitry is configured to receive a PATH message for a Label Switched Path (LSP) tunnel in a Multiprotocol Label Switching (MPLS) network with a specified DiffSery Traffic Engineering (DSTE) Class Type, determine the DSTE Class Type based on the PATH message, and store the DSTE Class Type for the LSP tunnel to ensure a Facility Bypass tunnel used for the LSP tunnel supports the specified DSTE Class Type. The circuitry can be further configured to, responsive to a failure of the LSP tunnel, select the Facility Bypass tunnel for the LSP tunnel such that the Facility Bypass tunnel supports the specified DSTE Class Type.