Abstract: The technology relates to using on-board sensor data, off-board information and a deep learning model to classify road wetness and/or to perform a regression analysis on road wetness based on a set of input information. Such information includes on-board and/or off-board signals obtained from one or more sources including on-board perception sensors, other on-board modules, external weather measurement, external weather services, etc. The ground truth includes measurements of water film thickness and/or ice coverage on road surfaces. The ground truth, on-board and off-board signals are used to build the model. The constructed model can be deployed in autonomous vehicles for classifying/regressing the road wetness with on-board and/or off-board signals as the input, without referring to the ground truth.

Abstract: One example system comprises a substrate and a waveguide disposed on the substrate to define an optical path on the substrate. The waveguide is configured to guide, inside the waveguide and along the optical path, a light signal toward an edge of the waveguide. The edge defines an optical interface between the waveguide and a fluidic optical medium adjacent to the edge of the waveguide. The system also includes an optical fluid and a fluid actuator configured to adjust a physical state of the optical fluid based on a control signal. The adjustment of the physical state of the optical fluid causes an adjustment of the fluidic optical medium adjacent to the edge.

Abstract: Aspects of the present disclosure relate generally to systems and methods for assessing validity of a map using image data collected by a laser sensor along a vehicle path. The method may compile image data received from the laser sensor. The map subject to assessment may define an area prohibiting entry by a vehicle.

Abstract: The technology relates to using on-board sensor data, off-board information and a deep learning model to classify road wetness and/or to perform a regression analysis on road wetness based on a set of input information. Such information includes on-board and/or off-board signals obtained from one or more sources including on-board perception sensors, other on-board modules, external weather measurement, external weather services, etc. The ground truth includes measurements of water film thickness and/or ice coverage on road surfaces. The ground truth, on-board and off-board signals are used to build the model. The constructed model can be deployed in autonomous vehicles for classifying/regressing the road wetness with on-board and/or off-board signals as the input, without referring to the ground truth.

Abstract: Methods and systems are disclosed for cross-validating a second sensor with a first sensor. Cross-validating the second sensor may include obtaining sensor readings from the first sensor and comparing the sensor readings from the first sensor with sensor readings obtained from the second sensor. In particular, the comparison of the sensor readings may include comparing state information about a vehicle detected by the first sensor and the second sensor. In addition, comparing the sensor readings may include obtaining a first image from the first sensor, obtaining a second image from the second sensor, and then comparing various characteristics of the images. One characteristic that may be compared are object labels applied to the vehicle detected by the first and second sensor. The first and second sensors may be different types of sensors.

Abstract: The present disclosure relates to systems and methods relating to the fabrication of light guide elements. An example system includes an optical component configured to direct light emitted by a light source to illuminate a photoresist material at one or more desired angles so as to expose an angled structure in the photoresist material. The photoresist material overlays at least a portion of a first surface of a substrate. The optical component includes a container containing a light-coupling material that is selected based in part on the one or more desired angles. The system also includes a reflective surface arranged to reflect at least a first portion of the emitted light to illuminate the photoresist material at the one or more desired angles.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a classifier to detect open vehicle doors. One of the methods includes obtaining a plurality of initial training examples, each initial training example comprising (i) a sensor sample from a collection of sensor samples and (ii) data classifying the sensor sample as characterizing a vehicle that has an open door; generating a plurality of additional training examples, comprising, for each initial training example: identifying, from the collection of sensor samples, one or more additional sensor samples that were captured less than a threshold amount of time before the sensor sample in the initial training example was captured; and training the machine learning classifier on first training data that includes the initial training examples and the additional training examples to generate updated weights for the machine learning classifier.

Abstract: Systems and methods are disclosed to identify a presence of a volumetric medium in an environment associated with a LIDAR system. In some implementations, the LIDAR system may emit a light pulse into the environment, receive a return light pulse corresponding to reflection of the emitted light pulse by a surface in the environment, and determine a pulse width of the received light pulse. The LIDAR system may compare the determined pulse width with a reference pulse width, and determine an amount of pulse elongation of the received light pulse. The LIDAR system may classify the surface as either an object to be avoided by a vehicle or as air particulates associated with the volumetric medium based, at least in part, on the determined amount of pulse elongation.

Abstract: The present disclosure relates to systems and methods involving Light Detection and Ranging (LIDAR or lidar) systems. Namely, an example method includes causing a light source of a LIDAR system to emit light along an emission vector. The method also includes adjusting the emission vector of the emitted light and determining an elevation angle component of the emission vector. The method further includes dynamically adjusting a per pulse energy of the emitted light based on the determined elevation angle component. An example system includes a vehicle and a light source coupled to the vehicle. The light source is configured to emit light along an emission vector toward an environment of the vehicle. The system also includes a controller operable to determine an elevation angle component of the emission vector and dynamically adjust a per pulse energy of the emitted light based on the determined elevation angle component.

Abstract: Simulated degraded sensor data may be generated for use in training a model. For instance, first sensor data collected by a sensor of a perception system of an autonomous vehicle may be received and converted into the simulated degraded sensor data for a particular degrading condition, such as a weather-related degrading condition. Then, the simulated degraded sensor data may be used to train a model for evaluating performance of the perception system to detect objects external to the autonomous vehicle under one or more conditions.

Abstract: The present disclosure relates to optical systems, vehicles, and methods that are configured to illuminate and image a wide field of view of an environment. An example optical system includes a camera having an optical axis and an outer lens element disposed along the optical axis. The optical system also includes a plurality of illumination modules, each of which includes at least one light-emitter device configured to emit light along a respective emission axis and a secondary optical element optically coupled to the at least one light-emitter device. The secondary optical element is configured to provide a light emission pattern having an azimuthal angle extent of at least 170 degrees so as to illuminate a portion of an environment of the optical system.

Abstract: An integrated hybrid rotary assembly is configured to provide power, torque and bi-directional communication to a rotatable sensor, such as a lidar, radar or optical sensor. A common ferrite core is shared by a motor, rotary transformer and radio frequency communication link. This hybrid configuration reduces cost, simplifies the manufacturing process, and can improve system reliability by employing a minimum number of parts. The assembly can be integrated with the sensor unit, which may be used in vehicles and other systems.

Abstract: Methods and devices for actively modifying a field of view of an autonomous vehicle in view of constraints are disclosed. In one embodiment, an example method is disclosed that includes causing a sensor in an autonomous vehicle to sense information about an environment in a first field of view, where a portion of the environment is obscured in the first field of view. The example method further includes determining a desired field of view in which the portion of the environment is not obscured and, based on the desired field of view and a set of constraints for the vehicle, determining a second field of view in which the portion of the environment is less obscured than in the first field of view. The example method further includes modifying a position of the vehicle, thereby causing the sensor to sense information in the second field of view.

Abstract: Aspects of the disclosure relate to controlling a vehicle. For instance, using a camera, a first camera image including a first object may be captured. A first bounding box for the first object and a distance to the first object may be identified. A second camera image including a second object may be captured. A second bounding box for the second image and a distance to the second object may be identified. Whether the first object is the second object may be determined using a plurality of models to compare visual similarity of the two bounding boxes, to compare a three-dimensional location based on the distance to the first object and a three-dimensional location based on the distance to the second object, and to compare results from the first and second models. The vehicle may be controlled in an autonomous driving mode based on a result of the third model.

Abstract: The present application relates to contact immersion lithography exposure units and methods of their use. An example contact exposure unit includes a container configured to contain a fluid material and a substrate disposed within the container. The substrate has a first surface and a second surface, and the substrate includes a photoresist material on at least the first surface. The contact exposure unit includes a photomask disposed within the container. The photomask is optically coupled to the photoresist material by way of a gap comprising the fluid material. The contact exposure unit also includes an inflatable balloon configured to be controllably inflated so as to apply a desired force to the second surface of the substrate to controllably adjust the gap between the photomask and the photoresist material.

Abstract: Aspects of the disclosure provide for enabling autonomous vehicles to pull over into driveways when picking up or dropping off passengers or goods. For instance, a request for a trip identifying a first location and a second location may be received. The first location may be a location of a client computing device, and the second location may be a starting location or a destination for the trip. A user preference for the trip indicating that a pickup for the trip be in a driveway may be identified. That the first location corresponds with the second location may be identified. Based on the determination that the first location corresponds with the second location, dispatch instructions may be to an autonomous vehicle. The dispatch instructions may identify a polygon for a driveway at the second location in order to cause the autonomous vehicle to pull over into the driveway.

Abstract: The disclosure relates to testing software for operating an autonomous vehicle. In one instance, a simulation may be run using log data collected by a vehicle operating in an autonomous driving mode. The simulation may be run using the software to control a simulated vehicle and by modifying a characteristic of an agent identified in the log data. During the running of the simulation, that a first type of interaction between the first simulated vehicle and the modified agent will occur may be determined. In response to determining that the particular type of interaction will occur, the modified agent may be replaced by a interactive agent that simulates a road user corresponding to the modified agent that is capable of responding to actions performed by simulated vehicles. That the particular type of interaction between the simulated vehicle and the interactive agent has occurred in the simulation may be determined.

Abstract: One example method of testing an electrical device comprises transmitting a data pattern to a memory device of the electrical device by a controller of the electrical device to provide a written data pattern to the memory device, wherein the data pattern replicates a resonant frequency of at least a portion of the electrical device, reading the written data pattern from the memory device with the controller, and comparing the written data pattern to the data pattern.

Abstract: Aspects of the disclosure provide for displaying notifications on a display of an autonomous vehicle. In one instance, a distance from the vehicle to a destination of the vehicle or a passenger may be determined. When the distance is between a first distance and a second distance, a first notification may be displayed on the display. The second distance may be less than the first distance. When the distance is less than the second distance, a second notification may be displayed on the display. The second notification provides additional information not provided by the first notification.

Abstract: The present disclosure relates to systems, vehicles, and methods for detecting optical defects in an optical path of a camera system. An example system may include an image sensor configured to provide images of a field of view via an optical path that extends through an optical window. The system also includes at least one phase-detection device and a controller. The controller is configured to execute instructions stored in the memory so as to carry out various operations, including receiving, from the image sensor, first pixel information indicative of an image of the field of view. The operations additionally include receiving, from the at least one phase-detection device, second pixel information indicative of a portion of the field of view. The operations yet further include determining, based on the first pixel information and the second pixel information, at least one optical defect associated with the optical path.