Abstract: Example embodiments relate to techniques that involve detecting and mitigating automotive interference. Electromagnetic signals propagating in the environment can be received by a radar unit that limits the signals received to a particular angle of arrival with reception antennas that limit the signals received to a particular polarization. Filters can be applied to the signals to remove portions that are outside an expected time range and an expected frequency range that depend on radar signal transmission parameters used by the radar unit. In addition, a model representing an expected electromagnetic signal digital representation can be used to remove portions of the signals that are indicative of spikes and plateaus associated with signal interference. A computing device can then generate an environment representation that indicates positions of surfaces relative to the vehicle using the remaining portions of the signals.

Abstract: Example implementations may relate to determining a strategy for a drop process associated with a light detection and ranging (LIDAR) device. In particular, the LIDAR device could emit light pulses and detect return light pulses, and could generate a set of data points representative of the detected return light pulses. The drop process could involve a computing system discarding data point(s) of the set and/or preventing emission of light pulse(s) by the LIDAR device. Accordingly, the computing system could detect a trigger to engage in the drop process, and may responsively (i) use information associated with the environment around the vehicle, operation of the vehicle, and/or operation of the LIDAR device as a basis to determine the strategy for the drop process, and (ii) engage in the drop process in accordance with the determined strategy.

Abstract: Aspects of the disclosure relate to repositioning a rooftop sensor of an autonomous vehicle when needed to reduce the overall height of the autonomous vehicle. For instance, while an autonomous vehicle is being controlled in an autonomous driving mode, a low clearance zone may be identified. An activation location may be determined based on the low clearance zone and a current speed of the autonomous vehicle. Once the activation location is reached by the autonomous vehicle, a motor may be caused to reposition the rooftop sensor. In addition, in some instances, after the autonomous vehicle has passed the low clearance zone, the motor may be caused to reposition the rooftop sensor again.

Abstract: Aspects of the disclosure provide a method of facilitating communications from an autonomous vehicle to a user. For instance, a method may include, while attempting to pick up the user and prior to the user entering an vehicle, inputting a current location of the vehicle and map information into a model in order to identify a type of communication action for communicating a location of the vehicle to the user; enabling a first communication based on the type of the communication action; determining whether the user has responded to the first communication from received sensor data; and enabling a second communication based on the determination of whether the user has responded to the communication.

Abstract: Aspects of the disclosure provide a method of processing trajectories. For instance, a planned trajectory may be received. A behavior prediction of the other road user may be received. For a sub portion of a plurality of sub portions of the planned trajectory, whether the sub portion conflicts with the behavior prediction of the other road user may be determined. When the sub portion is determined to conflict, whether the sub portion and the behavior prediction of the other road user meet at least one of a plurality of sets of preconditions may be determined. When the sub portion and the behavior prediction of the other road user are determined to meet at least one of the plurality of sets of preconditions, the planned trajectory may be annotated with a reaction for the other road user. The annotated planned trajectory may be used to control the autonomous vehicle.

Abstract: A composition that is easily applied, clear, well-bonded, and superhydrophobic is disclosed. In one aspect, the composition includes a hydrophobic fluorinated solvent, a binder comprising a hydrophobic fluorinated polymer, and hydrophobic fumed silica nanoparticles. Also disclosed is a structure including a substrate coated with the composition, as well as a method for making the composition and a method of coating a substrate with the composition.

Abstract: The present disclosure relates to optical systems and methods of their operation. An example optical system includes an optical component and one or more light sources configured to emit a light signal. The light signal interacts with the optical component so as to provide an interaction light signal. The optical system also includes a detector configured to detect at least a portion of the interaction light signal as a detected light signal. The optical system additionally includes a controller configured to carry out operations including causing the one or more light sources to emit the light signal and receiving the detected light signal from the detector. The operations also include determining, based on the detected light signal, that one or more defects are associated with the optical component.

Abstract: Methods and systems for associating labels between multiple sensors. One of the methods includes generating user interface presentation data that, when presented on a user device, causes the user device to display a user interface that: displays the images in the sequence of images and data identifying the first and second object tracks, and is configured to receive user inputs that associate first object tracks with second object tracks; and providing the user interface presentation data for presentation on the user device.

Abstract: Aspects of the disclosure provide for evaluation of a planned trajectory for an autonomous vehicle. For instance, for each of a plurality of objects, a predicted trajectory may be received. The planned trajectory may identify locations and times that the vehicle will be at those locations. For each of the plurality of objects, a grid including a plurality of cells may be generated. Occupancy of each grid for each of the plurality of objects may be determined based on the predicted trajectories. A cell of each grid which will be occupied by the vehicle at a location and time of the planned trajectory may be identified. The planned trajectory may be evaluated based on whether any identified cell is occupied by any of the plurality of objects at the time.

Abstract: Aspects of the present disclosure relate to protecting the privacy of a user of a dispatching service for driverless vehicles. For example, a request for a vehicle identifying user information is received. A client computing device may be identified based on the user information. In response to the request, a driverless vehicle may be dispatched to the location of the client device. Signaling information may be generated based on a set of rules including a first rule that the signaling information does not identify, indirectly or directly, the user as well as a second rule that the signaling information does not identify, indirectly or directly, the user information. The location of the client computing device and the signaling information may be sent to the driverless vehicle for display. In addition, the signaling information may also be sent to the client computing device for display.

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: The present disclosure relates to systems and methods that provide both an image of a scene and depth information for the scene. An example system includes at least one time-of-flight (ToF) sensor and an imaging sensor. The ToF sensor and the imaging sensor are configured to receive light from a scene. The system also includes at least one light source and a controller that carries out operations. The operations include causing the at least one light source to illuminate at least a portion of the scene with illumination light according to an illumination schedule. The operations also include causing the at least one ToF sensor to provide information indicative of a depth map of the scene based on the illumination light. The operations additionally include causing the imaging sensor to provide information indicative of an image of the scene based on the illumination light.

Abstract: The technology relates to generating simulations in order to evaluate software used to control vehicles in an autonomous driving mode. In one example, an initial situation involving a certain kind of interaction between a vehicle operating in the autonomous driving mode and an object may be identified. A search of log data may be conducted in order to identify one or more similar situations based on characteristics of the initial situation. A new simulation may be generated using the identified one or more similar situations by inserting the object into the one or more similar situations. The new simulation may be run in order to evaluate the software.

Abstract: Example embodiments relate to calibration systems for light detection and ranging (lidar) devices. An example calibration system includes a calibration target that includes a surface having at least one characterized reflectivity. The surface is configured to receive one or more calibration signals emitted by a lidar device along one or more optical axes when the lidar device is separated from the calibration target by an adjustable distance. The calibration system also includes at least one lens that modifies the one or more calibration signals. In addition, the system includes an adjustable attenuator configured to attenuate each of the one or more calibration signals to simulate, in combination with the at least one lens, a distance that is greater than the adjustable distance. Further, the system includes a calibration controller configured to analyze data associated with detected reflections of the one or more calibration signals.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for planning the future trajectory of an autonomous vehicle in an environment.

Abstract: A light detection and ranging (LIDAR) device includes a light emitter configured to emit light pulses into a field of view and a detector configured to detect light in the field of view. The light emitter emits a first light pulse. The detector detects, during a first measurement period, at least one reflected light pulse that is indicative of reflection by a retroreflector based on a shape of a reflected light pulse, a magnitude of a reflected light pulse, and/or a time separation between two reflected light pulses. In response to detecting the at least one reflected light pulse indicative of reflection by a retroreflector, the light emitter is deactivated for one or more subsequent measurement periods. Additionally, the LIDAR device may inform one or more other LIDAR devices by transmitting to a computing device information indicative of the retroreflector being within the field of view of the light emitter.