Abstract: Micro-LED structures include an LED epilayer that may be formed before the micro-LED structure is coupled to a backplane substrate. In order to prevent light leakage and maximize light output, the sidewalls and other surfaces of the LED epilayer may be coated with a reflective coating. For example, the reflective coating may include a metal layer that is electrically insulated between dielectric layers from the micro-LED electrodes. The reflective coating may also be formed using multiple layers in a distributed Bragg reflector configuration. This reflective coating may be formed during the LED fabrication process before the micro-LED structure is coupled to the backplane. The pixel isolation structures on the backplane may also include a reflective coating that is applied above the LED epilayers.

Abstract: Micro-LED structures include an LED epilayer that may be formed before the micro-LED structure is coupled to a backplane substrate. In order to prevent light leakage and maximize light output, the sidewalls and other surfaces of the LED epilayer may be coated with a reflective coating. For example, the reflective coating may include a metal layer that is electrically insulated between dielectric layers from the micro-LED electrodes. The reflective coating may also be formed using multiple layers in a distributed Bragg reflector configuration. This reflective coating may be formed during the LED fabrication process before the micro-LED structure is coupled to the backplane. The pixel isolation structures on the backplane may also include a reflective coating that is applied above the LED epilayers.

Abstract: Micro-LED structures include an LED epilayer that may be formed before the micro-LED structure is coupled to a backplane substrate. In order to prevent light leakage and maximize light output, the sidewalls and other surfaces of the LED epilayer may be coated with a reflective coating. For example, the reflective coating may include a metal layer that is electrically insulated between dielectric layers from the micro-LED electrodes. The reflective coating may also be formed using multiple layers in a distributed Bragg reflector configuration. This reflective coating may be formed during the LED fabrication process before the micro-LED structure is coupled to the backplane. The pixel isolation structures on the backplane may also include a reflective coating that is applied above the LED epilayers.

Abstract: Aspects of the disclosure provide methods of modeling wrong-way driving of road users. For instance, log data including an observed trajectory of a first road user may be accessed. A first set of candidate lane segments for wrong-way driving may be identified from map information. A second set of candidate lane segments for not wrong-way driving may be identified from the map information. For each candidate lane segment in the first set and in the second set, a distance cost between the candidate lane segment and the observed trajectory may be determined. A candidate lane segment may be selected from at least one of the first set or the second set based on the determined distance costs. The selected candidate lane segment may be used to train a model to provide a likelihood of a second road user being engaged in wrong-way driving in a lane.

Abstract: To operate an autonomous vehicle, a rail agent is detected in a vicinity of the autonomous vehicle using a detection system. One or more tracks are determined on which the detected rail agent is possibly traveling, and possible paths for the rail agent are predicted based on the determined one or more tracks. One or more motion paths are determined for one or more probable paths from the possible paths, and a likelihood for each of the one or more probable paths is determined based on each motion plan. A path for the autonomous vehicle is then determined based on a most probable path associated with a highest likelihood for the rail agent, and the autonomous vehicle is operated using the determined path.

Abstract: A method of forming a micro light-emitting diode (microLED) array may include forming pixel isolation structures on a sacrificial substrate, and mounting the microLEDs on a separate backplane. The processes that forms the pixel isolation structures, and which may damage the backplane or microLEDs can be separately performed on the sacrificial substrate. The pixel isolation structures can then be attached to the backplane and the sacrificial substrate can be removed. This allows the formation of the pixel isolation structures to be isolated, the microLEDs to be tested early in the process, and the interface between the microLEDs and subsequent layers to be free of adhesive.

Abstract: The technology relates to controlling a vehicle in an autonomous driving mode in accordance with behavior predictions for other road users in the vehicle's vicinity. In particular, the vehicle's onboard computing system may predict whether another road user will perform a “continuing” lane driving operation, such as going straight in a turn-only lane. Sensor data from detected/observed objects in the vehicle's nearby environment may be evaluated in view of one or more possible behaviors for different types of objects. In addition, roadway features, in particular whether lane segments are connected in a roadgraph, are also evaluated to determine probabilities of whether other road users may make an improper continuing lane driving operation. This is used to generate more accurate behavior predictions, which the vehicle can use to take alternative (e.g., corrective) driving actions.

Abstract: Aspects of the disclosure provide methods of modeling wrong-way driving of road users. For instance, log data including an observed trajectory of a first road user may be accessed. A first set of candidate lane segments for wrong-way driving may be identified from map information. A second set of candidate lane segments for not wrong-way driving may be identified from the map information. For each candidate lane segment in the first set and in the second set, a distance cost between the candidate lane segment and the observed trajectory may be determined. A candidate lane segment may be selected from at least one of the first set or the second set based on the determined distance costs. The selected candidate lane segment may be used to train a model to provide a likelihood of a second road user being engaged in wrong-way driving in a lane.

Abstract: To operate an autonomous vehicle, a rail agent is detected in a vicinity of the autonomous vehicle using a detection system. One or more tracks are determined on which the detected rail agent is possibly traveling, and possible paths for the rail agent are predicted based on the determined one or more tracks. One or more motion paths are determined for one or more probable paths from the possible paths, and a likelihood for each of the one or more probable paths is determined based on each motion plan. A path for the autonomous vehicle is then determined based on a most probable path associated with a highest likelihood for the rail agent, and the autonomous vehicle is operated using the determined path.

Abstract: The technology relates to controlling a vehicle in an autonomous driving mode in accordance with behavior predictions for other road users in the vehicle's vicinity. In particular, the vehicle's onboard computing system may predict whether another road user will perform a “continuing” lane driving operation, such as going straight in a turn-only lane. Sensor data from detected/observed objects in the vehicle's nearby environment may be evaluated in view of one or more possible behaviors for different types of objects. In addition, roadway features, in particular whether lane segments are connected in a roadgraph, are also evaluated to determine probabilities of whether other road users may make an improper continuing lane driving operation. This is used to generate more accurate behavior predictions, which the vehicle can use to take alternative (e.g., corrective) driving actions.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for agent trajectory prediction using candidate future intents.

Abstract: The present invention relates to the field of humidity-control materials, and in particular, to a long-acting humidity-control material for battery packs and a method for preparing same. The material comprises an upper packaging layer, a humidity-control layer, and a lower packaging layer. The humidity-control layer consists of a polyester fiber as a substrate and a modified humidity-control macromolecular coating. The prepared humidity-control material can achieve long-acting and long-distance control of humidity in the battery packs of vehicles and thereby avoid the moisture condensation in the battery packs, thus improving the operation safety and reliability of new energy vehicles.

Abstract: The present invention discloses a flame-retardant, thermal-insulating, and fireproof material for batteries, and relates to a silicone rubber flame-retardant and thermal-insulating material, which comprises a flame-retardant and thermal-insulating layer and an impact-resistant layer, wherein the flame-retardant and thermal-insulating layer comprises organic silicone rubber, a ceramic-forming filler, a flame retardant, an auxiliary agent, and glass powders with different initial melting temperatures, and molten-state temperature ranges of the glass powders cover 300° C. to 1500° C. Various glass powders with different molten-state temperature ranges are added to the material, so that when being burned to form a ceramic layer in the temperature range of 300° C. to 1500° C., the fireproof material always has glass powders in a molten state.

Abstract: The present disclosure provides devices and methods for repairing dice during micro-LED display fabrication. The devices include a backplane. The backplane has a plurality of backplane electrodes. Each backplane electrode includes a first material. A plurality of micro-LEDs having a plurality of micro-LED electrodes is included in the device. Each micro-LED electrode includes a second material. Each micro-LED electrode is bonded to each backplane electrode with an alloy of the first material and the second material therebetween. At least one backplane electrode is bonded to the micro-LED electrode via a repair material. The device includes a plurality of subpixel isolation (SI) structures formed over the backplane. The SI structures define wells of sub-pixels. Each well includes a respective micro-LED between adjacent SI structures. The sub-pixels have a color conversion material disposed in the wells.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing knowledge distillation for autonomous vehicles. One of the methods includes obtaining sensor data characterizing an environment, wherein the sensor data has been captured by one or more sensors on-board a vehicle in the environment; processing, for each of one or more surrounding agents in the environment, a network input generated from the sensor data using a neural network to generate an agent discomfort prediction that characterizes a level of discomfort of the agent; combining the one or more agent discomfort predictions to generate an aggregated discomfort score; and providing the aggregated discomfort score to a path planning system of the vehicle in order to generate a future path of the vehicle.

Abstract: Aspects of the disclosure provide for controlling a vehicle in an autonomous driving mode. For instance, sensor data for an object as well as a plurality of predicted trajectories may be received. Each predicted trajectory may represent a plurality of possible future locations for the object. A grid including a plurality of cells, each being associated with a geographic area, may be generated. Probabilities that the object will enter the geographic area associated with each of the plurality of cells over a period of time into the future may be determined based on the sensor data in order to generate a heat map. One or more of the plurality of predicted trajectories may be compared to the heat map. The vehicle may be controlled in the autonomous driving mode based on the comparison.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a task schedule for generating prediction data for different agents. In one aspect, a method comprises receiving data that characterizes an environment in a vicinity of a vehicle at a current time step, the environment comprising a plurality of agents; receiving data that identifies high-priority agents for which respective data characterizing the agents must be generated at the current time step; identifying available computing resources at the current time step; processing the data that characterizes the environment using a complexity scoring model to determine a respective complexity score for each of the high-priority agents; and determining a schedule for the current time step that allocates the generation of the data characterizing the high-priority agents across the available computing resources based on the complexity scores.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that obtain scene features in an environment that includes an autonomous vehicle, a first target agent, and a second target agent, and determines whether the first target agent is an emergency vehicle that is active at a current time point. In response to determining that the first target agent is an emergency vehicle that is active at the current time point, an input is generated from the scene features. The input can characterize the scene and indicate that the first target agent is an emergency vehicle that is active at the current time point. Also in response, the input can be processed using a machine learning model that is configured to generate a trajectory prediction output for the second target agent that characterizes predicted future behavior of the second target agent after the current time point.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting near-curb driving behavior. One of the methods includes obtaining agent trajectory data for an agent in an environment, the agent trajectory data comprising a current location and current values for a predetermined set of motion parameters of the agent; processing a model input generated from the agent trajectory data using a trained machine learning model to generate a model output comprising a prediction of whether the agent will exhibit near-curb driving behavior within a predetermined timeframe, wherein an agent exhibits near-curb driving behavior when the agent operates within a particular distance of an edge of a road in the environment; and using the prediction to generate a planned path for a vehicle in the environment.

Abstract: A method, apparatus, and a non-transitory computer-readable medium storing program code may be provided. The method may include obtaining a first scene space unit in which a dynamic scene element in a scene space is located at a first moment and obtaining a first photographing space unit in which a virtual camera is located in a photographing space at the first moment. The method may also include determining a visibility relationship between the first scene space unit and the first photographing space unit based on prestored visibility data. When the visibility relationship between the first scene space unit and the first photographing space unit is invisible, the method includes removing the dynamic scene element and obtaining remaining dynamic scene elements in the scene space. The method then renders the scene picture in the first moment.