Abstract: Systems and methods for enhanced object detection for autonomous vehicles based on field of view. An example method includes obtaining an image from an image sensor of one or more image sensors positioned about a vehicle. A field of view for the image is determined, with the field of view being associated with a vanishing line. A crop portion corresponding to the field of view is generated from the image, with a remaining portion of the image being downsampled. Information associated with detected objects depicted in the image is outputted based on a convolutional neural network, with detecting objects being based on performing a forward pass through the convolutional neural network of the crop portion and the remaining portion.

Abstract: A compliant mechanism is provided for monitoring the position of a suspension of a vehicle. The compliant mechanism can include a body for coupling to both an angle sensor and the suspension of the vehicle. The body can have at least two first portions and at least one second portion. The second portion is coupled to both of the two first portions and is more flexible than the two first portions.

Abstract: A processor retrieves data associated with a set of driving sessions and generates a training dataset by labeling a first subset of data that corresponds to driving sessions that included a first event and labeling a second subset of the data that corresponds to driving sessions that included an indication of an airbag activation. The processor then trains an artificial intelligence model using the training dataset, such that trained artificial intelligence model predicts a score indicative of a likelihood of a new driving session associated with a new driver being associated with at least the first event or an airbag activation. Once trained, the processor can augment the score using data retrieved after each driving session. The processor can also notify the driver if the driver's actions has caused their score to increase/decrease and provide an underlying reason.

Abstract: Sensor data, including a group of time series elements, is received. A training data set is determined, including by determining for at least a selected time series element in the group of time series elements a corresponding ground truth. The corresponding ground truth is based on a plurality of time series elements in the group of time series elements. A processor is used to train a machine learning model using the training dataset.

Abstract: A vehicular autonomous driving system includes a fault prediction unit, including a processor and memory, configured to predict a potential future fault condition by: monitoring performance data associated with the plurality of autonomous driving components; comparing the performance data associated with the plurality of autonomous driving components to a plurality of performance thresholds; and determining the potential future fault condition for one of the plurality of autonomous driving components, when the performance data associated with the one of the plurality of autonomous driving components compare unfavorably to corresponding one of the plurality of performance thresholds.

Abstract: An image captured using a sensor on a vehicle is received and decomposed into a plurality of component images. Each component image of the plurality of component images is provided as a different input to a different layer of a plurality of layers of an artificial neural network to determine a result. The result of the artificial neural network is used to at least in part autonomously operate the vehicle.

Abstract: An electronic assembly includes a mechanical carrier, a plurality of integrated circuits disposed on the mechanical carrier, a fan out package disposed on the plurality of integrated circuits, a plurality of singulated substrates disposed on the fan out package, a plurality of electronic components disposed on the plurality of singulated substrates, and at least one stiffness ring disposed on the plurality of singulated substrates. A method for constructing an electronic assembly includes identifying a group of known good singulated substrates, joining the group of known good singulated substrates into a substrate panel, attaching at least one bridge to the substrate panel that electrically couples at least two of the known good singulated substrates, and mounting a plurality of electronic components onto the substrate panel, each electronic component of the plurality of electronic components corresponding to a respective known good singulated substrate.

Abstract: A processor coupled to memory is configured to receive an identification of a geographical location associated with a target specified by a user remote from a vehicle. A machine learning model is utilized to generate a representation of at least a portion of an environment surrounding the vehicle using sensor data from one or more sensors of the vehicle. At least a portion of a path to a target location corresponding to the received geographical location is calculated using the generated representation of the at least portion of the environment surrounding the vehicle. At least one command is provided to automatically navigate the vehicle based on the determined path and updated sensor data from at least a portion of the one or more sensors of the vehicle.

Abstract: Systems and methods for texturing substrates (e.g., glass, metal, and the like) and the textured substrates produced using such systems and methods are disclosed. An exemplary system for texturing a substrate includes a first roller and a second roller. The first roller has a first textured surface. The first textured surface has a root mean square roughness between 40 to 1000 microns and an autocorrelation function greater than 0.5 for distances less than 50 microns.

Abstract: A system is comprised of one or more processors coupled to memory. The one or more processors are configured to receive image data based on an image captured using a camera of a vehicle and to utilize the image data as a basis of an input to a trained machine learning model to at least in part identify a distance of an object from the vehicle. The trained machine learning model has been trained using a training image and a correlated output of an emitting distance sensor.

Abstract: A metal sulfate manufacturing system comprising an electrochemical dissolution system having, an anode electrode that holds metal raw material, a cathode electrode, an electrolyte bath having an inlet to receive an initial acid or metal-acid complex solution and an outlet to discharge the treated metal sulfate solution, stirring equipment that mixes the electrolyte bath, a temperature control system, and a rectifier that supplies current at constant voltage between the anode and cathode electrode.

Abstract: An angle-detecting door handle assembly comprises: a handle member; a four-bar link configured to move the handle member between at least retracted and presented positions relative to a door surface; a motor configured to actuate the four-bar link; a rotary sensor configured to detect an angle of the four-bar link throughout actuation and generate a signal corresponding to the detected angle; and a controller configured to control the motor based on the signal from the rotary sensor.

Abstract: Dry process electrode films, and energy storage devices incorporating the same are described, including a silicon active material. The films may be free standing anode electrode films. Also provided are methods for fabricating such anode electrode films.

Abstract: Sensor data, including a group of time series elements, is received. A training data set is determined, including by determining for at least a selected time series element in the group of time series elements a corresponding ground truth. The corresponding ground truth is based on a plurality of time series elements in the group of time series elements. A processor is used to train a machine learning model using the training dataset.

Abstract: An energy storage device can include a first electrode, a second electrode and a separator between the first electrode and the second electrode wherein the first electrode includes an electrochemically active material and a porous carbon material, and the second electrode includes elemental lithium metal and carbon particles. A method for fabricating an energy storage device can include forming a first electrode and a second electrode, and inserting a separator between the first electrode and the second electrode, where forming the first electrode includes combining an electrochemically active material and a porous carbon material, and forming the second electrode includes combining elemental lithium metal and a plurality of carbon particles.

Abstract: A microprocessor system comprises a computational array and a hardware data formatter. The computational array includes a plurality of computation units that each operates on a corresponding value addressed from memory. The values operated by the computation units are synchronously provided together to the computational array as a group of values to be processed in parallel. The hardware data formatter is configured to gather the group of values, wherein the group of values includes a first subset of values located consecutively in memory and a second subset of values located consecutively in memory. The first subset of values is not required to be located consecutively in the memory from the second subset of values.

Abstract: Some examples relate to the configuration or management of an integrated component that provides structural component functionality for a vehicle, such as a cross member that absorbs loads placed on the vehicle. Additionally, the integrated component illustratively further provides air reservoir functionality that for one or more additional vehicle components. In some examples, an integrated component can provide structural component functionality associated with a cross member mounted between shock towers and air reservoir functionality to provide compression air such as for active or semi-active vehicle suspension systems.

Abstract: A valve includes a holder having an expandable material. The valve includes a retainer coupled to the holder. The valve further includes an umbrella member with a stem coupled to the holder. The expandable material is adapted to expand in size when absorbing a fluid and translate the umbrella member along an axis of the stem.

Abstract: Systems and methods for a global headlamp. An example method includes obtaining configuration information indicative of a jurisdiction associated with a vehicle. Headlamp state information is accessed which includes multiple headlamp states. A current headlamp state of the multiple headlamp states is determined based on the configuration information. A propagation is output via a pixelated light source in a headlamp of the vehicle, the propagation representing a particular beam pattern which is compliant with the jurisdiction.

Abstract: Systems and methods for enhanced object detection for autonomous vehicles based on field of view. An example method includes obtaining an image from an image sensor of one or more image sensors positioned about a vehicle. A field of view for the image is determined, with the field of view being associated with a vanishing line. A crop portion corresponding to the field of view is generated from the image, with a remaining portion of the image being downsampled. Information associated with detected objects depicted in the image is outputted based on a convolutional neural network, with detecting objects being based on performing a forward pass through the convolutional neural network of the crop portion and the remaining portion.