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: A method and apparatus are provided for optimizing one or more object detection parameters used by an autonomous vehicle to detect objects in images. The autonomous vehicle may capture the images using one or more sensors. The autonomous vehicle may then determine object labels and their corresponding object label parameters for the detected objects. The captured images and the object label parameters may be communicated to an object identification server. The object identification server may request that one or more reviewers identify objects in the captured images. The object identification server may then compare the identification of objects by reviewers with the identification of objects by the autonomous vehicle. Depending on the results of the comparison, the object identification server may recommend or perform the optimization of one or more of the object detection parameters.

Abstract: The disclosure relates to using ambient lighting conditions with passenger and goods pickups and drop offs with autonomous vehicles. For instance, a map of ambient lighting conditions for stopping locations may be generated by receiving ambient lighting condition data for predetermined stopping locations and arranging this data into a plurality of buckets based on time and one of the stopping locations. A vehicle may then be controlled in an autonomous driving mode in order to stop for a passenger by both observing ambient lighting conditions for different stopping locations and, in some instances, also using the map.

Abstract: Aspects of the present disclosure relate to a vehicle for maneuvering an occupant of the vehicle to a destination autonomously as well as providing information about the vehicle and the vehicle's environment for display to the occupant.

Abstract: Aspects of the present disclosure relate to a vehicle having one or more computing devices that may receive instructions to pick up a passenger at a pickup location and determine when the vehicle is within a first distance of the pickup location. When the vehicle is within the first distance, the computing devices may make a first attempt to find a spot to park the vehicle and wait for the passenger. When the vehicle is unable to find a spot to park the vehicle on the first attempt, the computing devices may maneuvering the vehicle in order to make a second attempt to find a spot to park the vehicle and wait for the passenger. When the vehicle is unable to find a spot to park the vehicle on the second attempt, the computing devices may stop the vehicle in a current lane to wait for the passenger.

Abstract: Aspects of the disclosure relate to enabling roadside assistance to a vehicle that requires assistance having an autonomous driving mode. For instance, a technician may be assigned to the vehicle that requires assistance. A signal corresponding to user input at a remote computing device requesting a change to a state of the vehicle may be received. The signal may be based on details of the assigned technician. Based on the validation, an instruction may be sent to the vehicle to change the state of the vehicle.

Abstract: Aspects of the technology relate to assisting a passenger in an autonomous vehicle without a driver. For instance, after a door of the vehicle is opened, a predetermined period of time may be waited by processors of computing devices of the vehicle. After waiting the predetermined period of time and when the vehicle's door remains open, a set of instructions for closing the vehicle's door may be played by the processors through a speaker of the vehicle. Once the door of the vehicle is closed, an announcement may be played by the processors through the speaker requesting that the passenger press a first button to initiate a ride to a destination. In response to the first button being pressed, the ride to the destination may be initiated by the processors by maneuvering the vehicle autonomously to the destination.

Abstract: Aspects of the disclosure relate to models for estimating the likelihood of fatigue in test drivers. In some instances, training data including videos of the test drivers while such test drivers are tasked with monitoring driving of a vehicle operating in an autonomous driving mode may be identified. The training data also includes driver drowsiness values generated from one or more human operators observing the videos. The training inputs and outputs may be used to train the model such that when a new video of a first test driver is input into the model, the model will output an estimate of a likelihood of fatigue for that test driver.

Abstract: Methods, systems, and apparatus, for an autonomous vehicle navigation maintenance system. In one aspect, an autonomous vehicle monitoring system includes a mounting surface located on an autonomous vehicle, and a thermal imaging system affixed to the mounting surface, the thermal imaging system including a thermal imaging camera, a replaceable filter, and a filter fixture configured to affix the replaceable filter to the thermal imaging camera and aligned with an optical axis of the thermal imaging camera, and where maintenance of the replaceable filter does not include re-calibrating the thermal imaging camera.

Abstract: Example embodiments relate to pulse energy plans for light detection and ranging (lidar) devices based on areas of interest and thermal budgets. An example lidar device includes a plurality of light emitters configured to emit light pulses into an environment in a plurality of different emission directions. The lidar device also includes circuitry configured to power the plurality of light emitters. Further, the lidar device includes a plurality of detectors configured to detect reflections of light pulses emitted by the plurality of light emitters. In addition, the lidar device includes a controller configured to (i) determine a pulse energy plan based on one or more regions of interest in the environment and a thermal budget and (ii) control the circuitry based on the pulse energy plan. The pulse energy plan specifies a pulse energy level for each light pulse emitted by each light emitter in the plurality of light emitters.

Abstract: The technology relates to determining whether a camera is occluded. For instance, an image may be captured using a camera having red, green, and blue pixels each including a photosensor. Output values for the photosensors of each of the red pixels, green pixels, and blue pixels may be determined for the images. The output values of the green pixels may be compared to one or more of the output values of the red pixels or the output values of the blue pixels. That the camera is occluded is determined based on the comparison.

Abstract: Aspects of the disclosure relate to generating a puddle occupancy grid including a plurality of cells. For instance, a first probability value for a puddle being located at a first location generated using sensor data from a first sensor may be received. A second probability value for a puddle being located at a second location generating using sensor data from a second sensor different from the first sensor may be received. A first cell may be identified from the plurality of cells using the first location. The first cell may also be identified using the second location. A value for the cell may be generated using the first probability value and the second probability value.

Abstract: An article including a durable, optically transparent, and superhydrophobic coating is described. In one aspect, the present disclosure provides a coating comprising a layer of aerogel disposed interstitially between spaced features extending in a direction perpendicular to a major surface of the coating, the spaced features having an average height of between 200-5000 nm and an average spacing of between 10-2000 nm, and comprising at least 75 wt. % of one or more of crystalline or amorphous silicon, an inorganic oxide, a polymer, crystalline or amorphous carbon, a carbide, or a nitride.

Abstract: Example embodiments relate to scheduling and processing sensor data across multiple digital signal processing (DSP) cores. A system may include DSP cores that are virtually arranged into a first segment and a second segment, each with DSP cores arranged in a linear order. The system may process sensor data using the DSP cores and a processing pipeline. DSP cores from the first segment are configured to initiate processing a first stage sequentially based on the linear order until all DSP cores are processing portions in parallel, collate outputs to produce a first stage output, and provide a first signal to the second segment based on producing the first stage output.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for sensor calibration with environment map. In some implementations, a three-dimensional surfel representation of a real-world environment is obtained. One or more surfels of the surfel representation having a particular classification of the different classifications are selected. Input sensor data from one or more sensors installed on an autonomous or semi-autonomous vehicle are received. The input sensor data is compared to the surfel representation to identify one or more differences between the observation and the surfel representation. At least one sensor of the one or more sensors is calibrated using the one or more differences between the observation and the surfel representation.

Abstract: The technology provides a seat release blocker that covers a seat release latching mechanism, where the latching mechanism would enable a passenger to fold down one or more seats of a vehicle. This can be particularly beneficial when the vehicle is operating in an autonomous driving mode, because certain areas within the vehicle may be restricted from passenger access. For instance, access to the trunk or cargo area may be limited to authorized service personnel. The seat release blocker includes a cover member that is fixedly secured to a seat such as a middle seat, using one or more fastener members such as a screw. Once the cover is releasably secured to the seat, the side of the cover with the fasteners may be completely or substantially covered by the side of an adjacent seat.

Abstract: Aspects of the disclosure provide for determining whether a vehicle is in a loop for an autonomous vehicle. For instance, a route from a current location of the vehicle to a destination for a trip may be generated. Locations traversed by the vehicle during the trip may be tracked. Locations of the route may be compared to the tracked locations to determine an overlap value. Whether the vehicle is in a loop may be determined based on the overlap value.

Abstract: Methods and devices for detecting traffic signals and their associated states are disclosed. In one embodiment, an example method includes a scanning a target area using one or more sensors of a vehicle to obtain target area information. The vehicle may be configured to operate in an autonomous mode, and the target area may be a type of area where traffic signals are typically located. The method may also include detecting a traffic signal in the target area information, determining a location of the traffic signal, and determining a state of the traffic signal. Also, a confidence in the traffic signal may be determined. For example, the location of the traffic signal may be compared to known locations of traffic signals. Based on the state of the traffic signal and the confidence in the traffic signal, the vehicle may be controlled in the autonomous mode.