Abstract: The technology relates to camera systems for vehicles having an autonomous driving mode. An example system includes a first camera mounted on a vehicle in order to capture images of the vehicle's environment. The first camera has a first exposure time and being without an ND filter. The system also includes a second camera mounted on the vehicle in order to capture images of the vehicle's environment and having an ND filter. The system also includes one or more processors configured to capture images using the first camera and the first exposure time, capture images using the second camera and the second exposure time, use the images captured using the second camera to identify illuminated objects, use the images captured using the first camera to identify the locations of objects, and use the identified illuminated objects and identified locations of objects to control the vehicle in an autonomous driving mode.

Abstract: The technology relates to autonomous vehicles suffering a breakdown along a roadway. Onboard systems may utilize various proactive operations to alert specific vehicles or other objects on or near the roadway about the breakdown. This can be done alternatively or in addition to turning on the hazard lights or calling for remote assistance. The disabled vehicle is able to detect nearby and approaching objects. The detection may be performed in combination with a determination of the type of object or predicted behavior for that object, enables the vehicle to generate a targeted alert that can be transmitted or otherwise presented to that particular object. This approach provides the other object, such as a vehicle, bicyclist or pedestrian, sufficient time and information about the breakdown to take appropriate corrective action. Different communication options are available and may be selected based on the particular object, environmental conditions and other factors.

Abstract: A neural network system for identifying positions of objects in an input image can include an object detector neural network, a memory interface subsystem, and an external memory. The object detector neural network is configured to, at each time step of multiple successive time steps, (i) receive a first neural network input that represents the input image and a second neural network input that identifies a first set of positions of the input image that have each been classified as showing a respective object of the set of objects, and (ii) process the first and second inputs to generate a set of output scores that each represents a respective likelihood that an object that is not one of the objects shown at any of the positions in the first set of positions is shown at a respective position of the input image that corresponds to the output score.

Abstract: A system includes a dome, a wiper assembly, a position sensor and a control device. The wiper assembly includes a wiper blade configured to rotate around the dome. The position sensor may be configured to send a signal to a control device when a wiper blade passes the position sensor. The control device may include one or more processors configured to receive the signal from the position sensor and determine a location of the wiper blade relative to the dome based on the received signal.

Abstract: A passenger in an automated vehicle may relinquish control of the vehicle to a control computer when the control computer has determined that it may maneuver the vehicle safely to a destination. The passenger may relinquish or regain control of the vehicle by applying different degrees of pressure, for example, on a steering wheel of the vehicle. The control computer may convey status information to a passenger in a variety of ways including by illuminating elements of the vehicle. The color and location of the illumination may indicate the status of the control computer, for example, whether the control computer has been armed, is ready to take control of the vehicle, or is currently controlling the vehicle.

Abstract: Aspects of the disclosure relate to testing predictions of an autonomous vehicle relating to another vehicle or object in a roadway. For instance, one or more processors may plan to maneuver the autonomous vehicle to complete an action and predict that the other vehicle will take a responsive action. The autonomous vehicle is then maneuvered towards completing the action in a way that would allow the autonomous vehicle to cancel completing the action without causing a collision between the first vehicle and the second vehicle, and in order to indicate to the second vehicle or a driver of the second vehicle that the first vehicle is attempting to complete the action. Thereafter, when the first vehicle is determined to be able to take the action, the action is completed by controlling the first vehicle autonomously using the determination of whether the second vehicle begins to take the particular responsive action.

Abstract: Examples described may enable provision of remote assistance for an autonomous vehicle. An example method includes a computing system operating by default in a first mode and periodically transitioning from operation in the first mode to operation in a second mode. In the first mode, the system may receive environment data provided by the vehicle and representing object(s) having a detection confidence below a threshold, where the detection confidence is indicative of a likelihood of correct identification of the object(s), and responsive to the object(s) having a confidence below the threshold, provide remote assistance data comprising an instruction to control the vehicle and/or a correct identification of the object(s). In the second mode, the system may trigger user interface display of remote assistor alertness data based on pre-stored data related to an environment in which the pre-stored data was acquired, and receive a response relating to the alertness data.

Abstract: Aspects of the disclosure relate to detecting unmapped drivable road surfaces. In one instance, sensor data captured by a sensor of an autonomous vehicle may be projected onto a grid having a plurality of cells. The plurality of cells may be classified by generating a label for each of the plurality of cells. Each label may identifies whether or not a corresponding cell contains a drivable surface. Ones of the plurality of cells may be clustered based on the labels to form a cluster of cells. An area of the cluster of cells may be compared to a map. Whether the area of the cluster of cells is an unmapped drivable road surface may be determined based on the comparison.

Abstract: Aspects of the disclosure relate to adjusting a shear pin to minimize an impact force felt by an object in a collision with a vehicle. For example, one or more second computing devices may receive, from one or more first computing devices, information indicating that an impact with an object is imminent. In response to the received information, the second computing devices may determine a first shear force for a first shear pin, wherein the first shear force is a desired amount of shear force necessary to break the first shear pin. The second computing devices may send a triggering signal to activate an actuator prior to an impact with the identified impact target. The actuator, in response to receiving the triggering signal, may adjust the first shear pin in a first pinhole, so the first shear pin will break at the first shear force.

Abstract: Example embodiments relate to multiple operating modes to expand dynamic range. An example embodiment includes a camera system. The camera system may include a first image sensor having a first dynamic range corresponding to a first range of luminance levels in a scene. The system may also include a second image sensor having a second dynamic range corresponding to a second range of luminance levels in the scene. The camera system may further include a processor coupled to the first image sensor and the second image sensor. The processor may be configured to execute instructions to identify objects of a first type in a first image of the scene captured by the first image sensor and identify objects of a second object type in a second image of the scene captured by the second image sensor.

Abstract: An antenna includes a plurality of waveguide antenna elements arranged in a first array configured to operate with a first polarization. The antenna also includes a plurality of waveguide output ports arranged in a second array configured to operate with a second polarization. The second polarization is different from the first polarization. The antenna further includes a polarization-modification layer with channels defined therein. The polarization-modification layer is disposed between the waveguide antenna elements and the waveguide output ports. The channels are oriented at a first angle with respect to the waveguide antenna elements and at a second angle with respect to the waveguide output ports. The channels are configured to receive input electromagnetic waves having the first polarization and transmit output electromagnetic waves having a first intermediate polarization.

Abstract: A computing system may operate a LIDAR device to emit light pulses in accordance with a time sequence including a time-varying dither. The system may then determine that the LIDAR detected return light pulses during corresponding detection periods for each of two or more emitted light pulses. Responsively, the system may determine that the detected return light pulses have (i) detection times relative to corresponding emission times of a plurality of first emitted light pulses that are indicative of a first set of ranges and (ii) detection times relative to corresponding emission times of a plurality of second emitted light pulses that are indicative of a second set of ranges. Given this, the system may select between using the first set of ranges as a basis for object detection and using the second set of ranges as a basis for object detection, and may then engage in object detection accordingly.

Abstract: Aspects of the disclosure relate to controlling a vehicle having an autonomous driving mode. This may include receiving, by one or more processors of the vehicle, first information identifying a current relative humidity measurement within a sensor housing of a vehicle having an autonomous driving mode. The relative humidity measurement and pre-stored environmental map information may be used by the one or more processors to estimate a condition of a sensor within the sensor housing at a future time. This estimated condition may be used by the one or more processors to control the vehicle.

Abstract: An example apparatus may include a first plate having a first side. A first plurality of fins may be integral with the first side of the first plate and protruding perpendicularly therefrom. The first plurality of fins may be arranged in first concentric circles separated radially by a first distance. The apparatus may also include a second plate having a first side. The second plate may be rotatably coupled to the first plate. A second plurality of fins may be integral with the first side of the second plate and protruding perpendicularly therefrom. The second plurality of fins may be arranged in second concentric circles separated radially by the first distance. Each fin of the second plurality of fins may interpose between adjacent fins of the first plurality of fins to transfer heat between the second plate and the first plate.

Abstract: The present disclosure relates to systems and methods directed to alignment of light-emitting devices. An example method includes coupling a support substrate to a light guide assembly. The support substrate includes a plurality of elongate structures and a plurality of laser diodes. Each laser diode of the plurality of laser diodes is coupled to a respective elongate structure of the plurality of elongate structures. The method also includes causing a given laser diode of the plurality of laser diodes to emit light toward the light guide assembly. The light guide assembly includes a light guide manifold configured to guide at least a portion of the emitted light as transmitted light. The method additionally includes comparing at least one optical characteristic of the transmitted light to a desired optical characteristic and, based on the comparison, adjusting a position of the given laser diode by adjusting the respective elongate structure.

Abstract: A communication system is disclosed. The system can include a first communication unit including a first antenna, a second communication unit including a second antenna and a dielectric waveguide cable, and a rotary joint configured to enable the first unit to rotate with respect to the second unit about an axis of rotation of the system. The dielectric waveguide cable can extend from the second antenna to the rotary joint, where a proximal end of the cable can be coupled to the second antenna and a distal end of the cable can be affixed to the second unit at a location bordering a space defined by the rotary joint. The first and second units can be configured to engage in two-way communication with each other. An axis of the distal end of the cable can be substantially aligned with the axis of rotation of the system.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a representation of a trajectory of a target agent in an environment. In one aspect, the representation of the trajectory of the target agent in the environment is a concatenation of a plurality of channels, where each channel is represented as a two-dimensional array of data values. Each position in each channel corresponds to a respective spatial position in the environment, and corresponding positions in different channels correspond to the same spatial position in the environment. The channels include a time channel and a respective motion channel corresponding to each motion parameter in a predetermined set of motion parameters.

Abstract: Aspects of the disclosure relate to an autonomous vehicle that may detected other nearby vehicles and identify them as parked or unparked. This identification may be based on visual indicia displayed by the detected vehicles as well as traffic control factors relating to the detected vehicles. Detected vehicles that are in a known parking spot may automatically be identified as parked. In addition, detected vehicles that satisfy conditions that are indications of being parked may also be identified as parked. The autonomous vehicle may then base its control strategy on whether or not a vehicle has been identified as parked or not.

Abstract: Aspects of the disclosure relate to classifying teh status of objects. For examples, one or more computing devices detect an object from an image of a vehicle's environment. The object is associated with a location. The one or more computing devices receive data corresponding to the surfaces of objects in the vehicle's environment and identifying data within a region around the location of the object. The one or more computing devices also determine whether the data within the region corresponds to a planar surface extending away from an edge of the object. Based on this determination, the one or more computing devices classify the status of the object.