Abstract: Aspects of the disclosure relate to identifying and adjusting speed plans for controlling a vehicle in an autonomous driving mode. In one example, an initial speed plan for controlling speed of the vehicle for a first predetermined period of time corresponding to an amount of time along a route of the vehicle is identified. Data identifying an object and characteristics of that object is received from a perception system of the vehicle. A trajectory for the object that will intersect with the route at an intersection point at particular point in time is predicted using the data. A set of constraints is generated based on at least the trajectory. The speed plan is adjusted in order to satisfy the set of constraints for a second predetermined period of time corresponding to the amount of time. The vehicle is maneuvered in the autonomous driving mode according to the adjusted speed plan.

Abstract: The present disclosure relates to systems and methods that facilitate light detection and ranging operations. An example transmit block includes at least one substrate with a plurality of angled facets. The plurality of angled facets provides a corresponding plurality of elevation angles. A set of angle differences between adjacent elevation angles includes at least two different angle difference values. A plurality of light-emitter devices is configured to emit light into an environment along the plurality of elevation angles toward respective target locations so as to provide a desired resolution and/or a respective elevation angle. The present disclosure also relates to adjusting shot power and a shot schedule based on the desired resolution and/or a respective elevation angle.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for selecting locations in an environment of a vehicle where objects are likely centered and determining properties of those objects. One of the methods includes receiving an input characterizing an environment external to a vehicle. For each of a plurality of locations in the environment, a respective first object score that represents a likelihood that a center of an object is located at the location is determined. Based on the first object scores, one or more locations from the plurality of locations are selected as locations in the environment at which respective objects are likely centered. Object properties of the objects that are likely centered at the selected locations are also determined.

Abstract: Aspects of the disclosure relate to controlling a first vehicle in an autonomous driving mode. While doing so, a second vehicle may be identified. Geometry for a future trajectory of the first vehicle may be identified, and an initial allowable discomfort value may be identified. Determining a speed profile for the geometry that meets the value may be attempted by determining a discomfort value for the speed profile based on a set of factors relating to at least discomfort of a passenger of the first vehicle and discomfort of a passenger of the second vehicle. When a speed profile that meets the value cannot be determined, the value may be adjusted until a speed profile that meets the value is determined. The speed profile that meets an adjusted value is used to control the first vehicle in the autonomous driving mode.

Abstract: A computing system may operate a LIDAR device to emit and detect light pulses in accordance with a time sequence including standard detection period(s) that establish a nominal detection range for the LIDAR device and extended detection period(s) having durations longer than those of the standard detection period(s). The system may then make a determination that the LIDAR detected return light pulse(s) during extended detection period(s) that correspond to particular emitted light pulse(s). Responsively, the computing system may determine that the detected return light pulse(s) have detection times relative to corresponding emission times of particular emitted light pulse(s) that are indicative of one or more ranges. Given this, the computing system may make a further determination of whether or not the one or more ranges indicate that an object is positioned outside of the nominal detection range, and may then engage in object detection in accordance with the further determination.

Abstract: Aspects of the disclosure relate to determining whether a feature of map information. For example, data identifying an object detected in a vehicle's environment and including location coordinates is received. This information is used to identify a corresponding feature from pre-stored map information based on a map location of the corresponding feature. The corresponding feature is defined as a curve and associated with a tag identifying a type of the corresponding object. A tolerance constraint is identified based on the tag. The curve is divided into two or more line segments. Each line segment has a first position. The first position of a line segment is changed in order to determine a second position based on the location coordinates and the tolerance constraint. A value is determined based on a comparison of the first position to the second position. This value indicates a likelihood that the corresponding feature has changed.

Abstract: Aspects of the present disclosure relate to context aware stopping of a vehicle without a driver. As an example, after a passenger has entered the vehicle, the vehicle is maneuvered by one or more processors in an autonomous driving mode towards a destination location along a route. The route is divided into two or more stages. A signal is received by the one or more processors. The signal indicates that the passenger is requesting that the vehicle stop or pull over. In response to the signal, the one or more processors determine a current stage of the route based on a current distance of the vehicle from a pickup location where the passenger entered the vehicle or a current distance of the vehicle from the destination location. The one or more processors then stop the vehicle in accordance with the determined current stage.

Abstract: Examples relating to vehicle radar systems are described. An example radar system may include a radar transmission unit located on a top portion of a vehicle configured to transmit an omnidirectional radar signal. The system may also include a radar unit comprising a plurality of radar reception arrays. The radar unit may be configured to rotate around an axis and receive radar reflections by one or more of the radar reception arrays. Additionally, the system may include a processing unit. The processing unit may be configured to process the received radar reflections to determine reflection information and control the vehicle based on the determined reflection information.

Abstract: Example embodiments relate to calibration systems usable for distortion characterization in cameras. An example embodiment includes a calibration system. The calibration system includes a first calibration target that includes a first mirror, a plurality of fiducials positioned on or adjacent to the first mirror, and an indexing fiducial positioned on or adjacent to the first mirror. The calibration system also includes a second calibration target that includes one or more second mirrors and has an aperture defined therein. The first mirror and the one or more second mirrors are separated by a distance. The first mirror faces the one or more second mirrors. The indexing fiducial is visible through the aperture in the second calibration target. Reflections of the plurality of fiducials are visible through the aperture defined in the second calibration target. The reflections of the plurality of fiducials are iterated reflections.

Abstract: A vehicle may receive one or more images of an environment of the vehicle. The vehicle may also receive a map of the environment. The vehicle may also match at least one feature in the one or more images with corresponding one or more features in the map. The vehicle may also identify a given area in the one or more images that corresponds to a a portion of the map that is within a threshold distance to the one or more features. The vehicle may also compress the one or more images to include a lower amount of details in areas of the one or more images other than the given area. The vehicle may also provide the compressed images to a remote system, and responsively receive operation instructions from the remote system.

Abstract: Aspects of the disclosure relate to reducing replacing a desiccant cartridge based upon a condensation risk. In one example, first information corresponding to a current dew point within a sensor housing of a sensor and second information identifying temperature data corresponding to a predefined area where the sensor is projected to travel may be received. Based upon the first and second information a condensation risk corresponding to the likelihood of condensation forming within the sensor housing in the event it traveled within the predefined area based upon the current dew point and the temperature data may be determined. Based upon the determined condensation risk, an indication that a desiccant cartridge within the sensor housing should be replaced to reduce the current dew point and the condensation risk may be provided.

Abstract: The technology relates to determining a future heading of an object. In order to do so, sensor data, including information identifying a bounding box representing an object in a vehicle's environment and locations of sensor data points corresponding to the object, may be received. Based on dimensions of the bounding box, an area corresponding to a wheel of the object may be identified. An orientation of the wheel may then be estimated based on the sensor data points having locations within the area. The estimation may then be used to determine a future heading of the object.

Abstract: The disclosure provides for a system. The system may include a rotational control system configured to rotate a seat of a vehicle, and one or more computing devices. The one or more computing devices may have one or more processors that are configured to determine that an impact is imminent at a location on the vehicle along a collision axis. A most favorable orientation may be determined by the one or more processors based on the determined location and collision axis. Using the rotational control system, the one or more processors may rotate the seat of the vehicle to the most favorable orientation in order to reduce risks of serious injury to a passenger in the seat caused by the imminent impact. A translational control system may be used by the one or more processors to translate the seat of the vehicle to a position relative to the determined location.

Abstract: The present disclosure relates to optical systems and related devices, specifically those related to light detection and ranging (LIDAR) systems. An example optical system includes a housing, a shaft defining a rotational axis, and a rotatable optical component coupled to the shaft. The optical system also includes a first rotary bearing having an inner race, an outer race, and a plurality of rolling elements configured to roll between the inner race and the outer race. The inner race is coupled to the shaft and the outer race is coupled to the housing. The optical system also includes a preload mechanism having a spring coupled to the housing and a preload distributor coupled to the spring and the outer race. The spring is configured to apply an axial preload force to the outer race through the preload distributor.

Abstract: The present disclosure relates to limitation of noise on light detectors using an aperture. One example implementation includes a system. The system includes a lens that focuses light from a scene toward a focal plane. The system also includes an aperture defined within an opaque material. The system also includes a plurality of waveguides. A given waveguide of the plurality has an input end that receives a portion of light transmitted through the aperture, and guides the received portion toward an output end of the given waveguide. A cross-sectional area of the guided portion at the output end is greater than a cross-sectional area of the received portion at the input end. The system also includes an array of light detectors that detects the guided light transmitted through the output end.

Abstract: The disclosure provides for a wiper system for cleaning a surface of a sensor housing, such as a sensor housing positioned on top of a vehicle. The wiper system includes a plurality of windows spaced around a sensor housing, and a plurality of wipers positioned around the sensor housing, each of the wipers includes a wiper blade configured to clean a corresponding window of the plurality of windows. The wiper system further includes a drive system including a movable part coupled to a motor. The motor is configured to drive the drive system to simultaneously rotate the plurality of wipers around the sensor housing such that the plurality of wipers remove debris from the plurality of windows.

Abstract: This technology relates to a system for clearing a sensor cover. The system may be comprised of a first wiper and second wiper configured to clear the sensor cover of debris and a motor. The motor may rotate the first wiper and the second wiper in a first direction at a first predetermined rotation rate defined at least in part by a second predetermined rotation rate of a first sensor arranged within the sensor cover. The first wiper and the second wiper may be offset by a predetermined angular distance relative to a center of the sensor cover.

Abstract: Methods and systems are disclosed for determining sensor degradation by actively controlling an autonomous vehicle. Determining sensor degradation may include obtaining sensor readings from a sensor of an autonomous vehicle, and determining baseline state information from the obtained sensor readings. A movement characteristic of the autonomous vehicle, such as speed or position, may then be changed. The sensor may then obtain additional sensor readings, and second state information may be determined from these additional sensor readings. Expected state information may be determined from the baseline state information and the change in the movement characteristic of the autonomous vehicle. A comparison of the expected state information and the second state information may then be performed. Based on this comparison, a determination may be made as to whether the sensor has degraded.