Abstract: Aspects of the disclosure provide for determining when to provide and providing secondary disengage alerts for a vehicle having autonomous and manual driving modes. For instance, while the vehicle is being controlled in the autonomous driving mode, user input is received at one or more user input devices of the vehicle. In response to receiving the user input, the vehicle may be transitioned from the autonomous driving mode to a manual driving mode and provide a primary disengage alert to an occupant of the vehicle regarding the transition. Whether to provide a secondary disengage alert may be determined based on at least circumstances of the user input. After the transition, the secondary disengage alert may be provided based on the determination.

Abstract: Example embodiments relate to pedestrian countdown signal classification to increase pedestrian behavior legibility. An example embodiment includes a method that includes obtaining, by a computing system of a vehicle, a camera image patch. The method further includes determining, by the computing system, using the camera image patch and a pedestrian countdown signal classifier model, a state of a pedestrian countdown signal. The method also includes determining, by the computing system based on the state of the pedestrian countdown signal, a prediction of whether a pedestrian will enter a crosswalk governed by the pedestrian countdown signal. And the method includes, based on the prediction, causing, by the computing system, the vehicle to perform an invitation action that invites a pedestrian to enter the crosswalk.

Abstract: The technology relates to assisting large self-driving vehicles, such as cargo vehicles, as they maneuver towards and/or park at a destination facility. This may include a given vehicle transitioning between different autonomous driving modes. Such a vehicles may be permitted to drive in a fully autonomous mode on certain roadways for the majority of a trip, but may need to change to a partially autonomous mode on other roadways or when entering or leaving a destination facility such as a warehouse, depot or service center. Large vehicles such as cargo truck may have limited room to maneuver in and park at the destination, which may also prevent operation in a fully autonomous mode. Here, information from the destination facility and/or a remote assistance service can be employed to aid in real-time semi-autonomous maneuvering.

Abstract: A method is provided that includes a vehicle receiving data from an external computing device indicative of at least one other vehicle in an environment of the vehicle. The vehicle may include a sensor configured to detect the environment of the vehicle. The at least one other vehicle may include at least one sensor. The method also includes determining a likelihood of interference between the at least one sensor of the at least one other vehicle the sensor of the vehicle. The method also includes initiating an adjustment of the sensor to reduce the likelihood of interference between the sensor of the vehicle and the at least one sensor of the at least one other vehicle responsive to the determination.

Abstract: A method includes identifying mass distribution data of an autonomous vehicle (AV). The mass distribution data is associated with a first load proximate a first distal end of a first axle of the AV and a second load proximate a second distal end of the first axle of the AV. The method further includes determining, based on the mass distribution data, one or more handling maneuver limits for the AV. The method further includes causing the AV to travel a route based on the one or more handling maneuver limits.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for evaluating a behavior prediction system.

Abstract: Aspects of the disclosure relate to controlling a vehicle in an autonomous driving mode. The system includes a plurality of sensors configured to generate sensor data. The system also includes a first computing system configured to generate trajectories using the sensor data and send the generated trajectories to a second computing system. The second computing system is configured to cause the vehicle to follow a receive trajectory. The system also includes a third computing system configured to, when there is a failure of the first computer system, generate and send trajectories to the second computing system based on whether a vehicle is located on a highway or a surface street.

Abstract: Systems and methods are described that relate to a light detection and ranging (LIDAR) device. The LIDAR device includes a fiber laser configured to emit light within a wavelength range, a scanning portion configured to direct the emitted light in a reciprocating manner about a first axis, and a plurality of detectors configured to sense light within the wavelength range. The device additionally includes a controller configured to receive target information, which may be indicative of an object, a position, a location, or an angle range. In response to receiving the target information, the controller may cause the rotational mount to rotate so as to adjust a pointing direction of the LIDAR. The controller is further configured to cause the LIDAR to scan a field-of-view (FOV) of the environment. The controller may determine a three-dimensional (3D) representation of the environment based on data from scanning the FOV.

Abstract: A camera includes a camera focus adjustment device, a lens, and an image sensor coupled to the camera focus adjustment device. The camera focus adjustment device includes a flexure structure. The flexure structure includes an outer framework of structural members continuously interconnected by flexure notch hinges. The flexure structure also includes two inner structural members oriented in parallel and extending from the outer framework of structural members. A gap is between the two inner structural members. The camera focus adjustment device also includes a piezoelectric material within the gap and a pair of wedges within the gap. The pair of wedges is affixed to the piezoelectric material and to one inner structural member of the two inner structural members. Based on temperature-based piezoelectric activity associated with the piezoelectric material, the camera focus adjustment device is operable to move the image sensor relative to the lens.

Abstract: Aspects of the disclosure relate to routing an autonomous vehicle. For instance, the vehicle may be maneuvered along a route in a first lane using map information identifying a first plurality of nodes representing locations within the first lane and a second plurality of nodes representing locations within a second lane different from the first lane. While maneuvering, when the vehicle should make a lane change may be determined by assessing a cost of connecting a first node of the first plurality of nodes with a second node of a second plurality of nodes. The assessment may be used to make the lane change from the first lane to the second lane.

Abstract: A system and method are arranged to provide recommendations to a user of a vehicle. In one aspect, the vehicle navigates in an autonomous mode and the sensors provide information that is based on the location of the vehicle and output from sensors directed to the environment surrounding the vehicle. In further aspects, both current and previous sensor data is used to make the recommendations, as well as data based on the sensors of other vehicles.

Abstract: A method and a radar system are provided in the present disclosure. The radar system includes a radar unit having an antenna array configured to transmit and receive radar signal and a memory configured to store radar calibration parameters and radar channel parameters corresponding to the radar unit. The method provides for operation of the radar system. The radar system also includes a radar processor. The radar processor is configured to cause transmission of radar signals by the antenna array based on the radar channel parameters. The radar processor is also configured to process received radar signals based on the radar calibration parameters. The radar system further includes a central vehicle controller configured to operate a vehicle based on the processed radar signals.

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. The information includes a representation of a scene depicting an external environment of the vehicle. The representation of the scene includes a visual representation of the vehicle and a visual representation of objects in an external environment of the vehicle.

Abstract: Example embodiments relate to techniques for implementing radar waveform diversity. A technique may involve a radar unit transmitting radar signals into an environment of a vehicle based on a code sequence that indicates a ramp direction and a phase shift for each pulse in a pulse used by the radar unit and receiving radar reflections from the environment. In some instances, the radar unit may leverage antennas in a multiple input multiple output (MIMO) arrangement to further add diversity to transmissions according to spatial code in the code sequence. The technique can further involve using a demodulator to map the environment based on the radar reflections and controlling the vehicle based on the mapping. In some instances, the code sequence is received from a system that is wirelessly providing orthogonal code sequences to multiple emitters.

Abstract: Example embodiments relate to real-time health monitoring for automotive radars. A computing device may receive radar data from multiple radar units that have partially overlapping fields of view and detect a target object located such that the radar units both capture measurements of the target object. The computing device may determine a power level representing the target object for radar data from each radar unit, adjust these power levels, and determine a power difference between them. When the power difference exceeds a threshold power difference, the computing device may perform a calibration process to decrease the power difference below the threshold power difference or alert the vehicle, including onboard algorithms, to the reduced performance of the radar.

Abstract: Aspects of the present disclosure relate to differentiating between active and inactive construction zones. In one example, this may include identifying a construction object associated with a construction zone. The identified construction object may be used to map the area of the construction zone. Detailed map information may then be used to classify the activity of the construction zone. The area of the construction zone and the classification may be added to the detailed map information. Subsequent to adding the construction zone and the classification to the detailed map information, the construction object (or another construction object) may be identified. The location of the construction object may be used to identify the construction zone and classification from the detailed map information. The classification of the classification may be used to operate a vehicle having an autonomous mode.

Abstract: An autonomous vehicle is provided that includes one or more sensors coupled to the autonomous vehicle, and a computing device configured to: (i) receive, from the one or more sensors, operational data related to an operation of the autonomous vehicle, (ii) receive geographical data related to an anticipated route of the autonomous vehicle, (iii) generate, for the anticipated route and based on the operational data and the geographical data, an operational response model representing respective operational constraints for one or more operational parameters of the autonomous vehicle, wherein values for the one or more operational parameters are represented along coordinate axes of a geometrical shape, and wherein the one or more operational parameters are mutually coupled to each other, and (iv) responsively execute, based on the operational response model, an autonomous control strategy comprising one or more adjustments to the operation of the vehicle within the respective operational constraints.

Abstract: Aspects of the disclosure provide for generating a visualization of a three-dimensional (3D) world view from the perspective of a camera of a vehicle. For example, images of a scene captured by a camera of the vehicle and 3D content for the scene may be received. A virtual camera model for the camera of the vehicle may be identified. A set of matrices may be generated using the virtual camera model. The set of matrices may be applied to the 3D content to create a 3D world view. The visualization may be generated using the 3D world view as an overlay with the image, and the visualization provides a real-world image from the perspective of the camera of the vehicle with one or more graphical overlays of the 3D content.