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: 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: 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: 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: 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: 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: 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: 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: 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.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating object predictions using a neural network. One of the methods includes receiving respective projections of a plurality of channels of input sensor data, wherein each channel of input sensor data represents different respective characteristics of electromagnetic radiation reflected off of one or more objects. Each of the projections of the plurality of channels of input sensor data are provided to a neural network subsystem trained to receive projections of input sensor data as input and to provide an object prediction as an output. At the output of the neural network subsystem, an object prediction that predicts a region of space that is likely to be occupied by an object is received.

Abstract: Example methods and systems for calibrating sensors using road map data are provided. An autonomous vehicle may use various vehicle sensors to assist in navigation. Within examples, the autonomous vehicle may calibrate vehicle sensors through performing a comparison or analysis between information about the environment received by sensors with similar information provided by map data (e.g., a road map). The autonomous vehicle may compare object locations as provided by the sensors and as shown by map data. Based on the comparison, the autonomous vehicle may adjust various sensors to accurately reflect the information as provided by the road map. In some instances, the autonomous vehicle may adjust the position, height, orientation, direction-of-focus, scaling, or other parameters of a sensor based on the information provided by a road map.

Abstract: Aspects of the present disclosure relate to a vehicle for maneuvering a passenger to a destination autonomously. The vehicle includes one or more computing devices that receive a request for a vehicle from a client computing device. The request identifies a first location. The one or more computing devices also determine whether the first location is within a threshold outside of a service area of the vehicle. When the location is within the threshold distance outside of the service area of the vehicle, the one or more computing devices identify a second location within the service area of the vehicle where the vehicle is able to stop for a passenger and based on the first location. The one or more computing devices then provide a map and a marker identifying the position of the second location on the map for display on the client computing device.

Abstract: Aspects of the disclosure provide systems and methods for providing suggested locations for pick up and destination locations. Pick up locations may include locations where an autonomous vehicle can pick up a passenger, while destination locations may include locations where the vehicle can wait for an additional passenger, stop and wait for a passenger to perform some task and return to the vehicle, or for the vehicle to drop off a passenger. As such, a request for a vehicle may be received from a client computing device. The request may identify a first location. A set of one or more suggested locations may be selected by comparing the predetermined locations to the first location. The set may be provided to the client computing device.

Abstract: In some implementations, an autonomous or semi-autonomous vehicle is capable of using a collision prediction system to determine a confidence that any objects detected within a vicinity of the vehicle are on a trajectory that will collide with the vehicle. Laser obstacle points derived from recent sensor readings of one or more sensors of a vehicle are initially obtained. The laser obstacle points are projected into a pose coordinate system to generate an occupancy grid of a vicinity of the vehicle. A confidence that any objects represented by the laser obstacle points are on a trajectory that will collide with the vehicle is determined by applying a particle filter to the occupancy grid.

Abstract: Aspects of the disclosure provide for a method for identifying speed limit signs and controlling an autonomous vehicle in response to detected speed limit signs. The autonomous vehicle's computing devices identifies a speed limit sign in a vehicle's environment and a location and orientation corresponding to the speed limit sign. Then, the and orientation location of the speed limit sign is determined to not correspond to a pre-stored location and a pre-stored orientation of a speed limit sign that is pre-stored in map information. An effect zone of the speed limit sign is determined based on the location and orientation of the speed limit sign and characteristics of surrounding areas or other detected object before or after the speed limit sign. The autonomous vehicle's computing devices determines a response of the vehicle based on the determined effect zone, and controls the autonomous vehicle based on the determined response.

Abstract: The disclosure relate to testing software for operating an autonomous vehicle. For instance, a first simulation may be run using log data and the software to control a first simulated vehicle. During this, one or more characteristics of the simulated vehicle may be compared with one or more characteristics of a vehicle from the log data. The comparison may be used to determine a divergence point for starting a timer. In addition, a second simulation may be run using the log data and the software to control a second simulated vehicle. The divergence point may be used to determine a handover time to allow the software to take control of the second simulated vehicle. Whether the software is able to continue through the first simulation before the timer expires without a particular type of event occurring and/or the second simulation without the particular type of event occurring is determined.

Abstract: The technology relates to controlling a vehicle in an autonomous driving mode, the method. For instance, a vehicle may be maneuvered in the autonomous driving mode using pre-stored map information identifying traffic flow directions. Data may be received from a perception system of the vehicle identifying objects in an external environment of the vehicle related to a traffic redirection not identified the map information. The received data may be used to identify one or more corridors of a traffic redirection. One of the one or more corridors may be selected based on a direction of traffic flow through the selected corridor. The vehicle may then be controlled in the autonomous driving mode to enter and follow the selected one of the one or more corridors based on the determined direction of flow of traffic through each of the one or more corridors.