Abstract: Junction queueing for vehicles is described, in which vehicles may be queued based on arrival time at a junction, position relative to a stopping location at the junction, and/or an amount of time waiting for other vehicles to proceed through the junction (timeout). In some examples, the queue may be first generated based on the arrival times of any other vehicle relative to a particular vehicle generating the queue. The queue may be updated based on arrival times of other vehicles (e.g., after the particular vehicle), whether another vehicle has proceeded out-of-turn (e.g., based on a position at the junction), and/or a timeout for vehicles that wait for others to yield at the junction. In some examples, hysteresis and alterations of the score for safety reasons may alter queue order. The queue may be used to control the particular vehicle to traverse the junction.

Abstract: A system and method for determining whether a passenger is seated in a seating area and, based at least in part on detecting the passenger, engaging or disengaging a flap in a headrest. Such a headrest may span multiple seats so that a single headrest is used by multiple passengers. Each of one or more flaps in the single headrest may then be configured by the passenger to provide each passenger with their own privacy and comfort. By actively controlling the state of the flap, a uniform passenger experience may be created so that the flap is in the same state upon a passenger entering the vehicle. Further, examples of the headrest are designed and configured to couple directly, or indirectly, to a vehicle body, such that the headrest does not couple directly to a seat or passenger seating area.

Abstract: A wireless-charging adapter is connectable to a direct current (DC) fast charger and includes an induction coil for wireless charging a second induction coil on a vehicle. In some instances, the adapter may include an electrical connector to mate with a DC fast charger. In addition, the adapter may include hardware and/or software to receive a DC from the DC fast charger and provide an alternating current (AC) to the induction coil. The induction coil of the adapter may be positioned (e.g., on a ground surface) to align with an induction coil on a vehicle.

Abstract: Techniques are discussed herein for determining truncated simulation regions within a parameter space of simulation scenarios, such as driving scenarios used to analyze and evaluate the responses of autonomous vehicle controllers. Using non-sampling-based parameter selection techniques, parameterized scenarios may be executed as simulations to determine the truncated simulation region. Sampling-based parameter selection techniques may be used to determine additional parameterized scenarios, which may be compared to the truncated simulation region. Parameterized scenarios within the truncated simulation region may be executed as simulations and scenarios outside of the truncated simulation region may be excluded, and the aggregated results may be analyzed to determine scenario/vehicle performance metrics across the scenario parameter space.

Abstract: A vehicle computing system may identify an obstruction along a route of travel and may connect to a service computing device for guidance. The service computing device may include a guidance system configured to receive waypoint and/or orientation input from an operator. The operator may evaluate the scenario and determine one or more waypoints and/or associated orientations for the vehicle to navigate the scenario. In some examples, the guidance system may validate the waypoint(s) and/or associated orientation(s). The service computing device may send the waypoint(s) and/or associated orientation(s) to the vehicle computing system. The vehicle computing system may validate the waypoint(s) and/or associated orientation(s) and, based on the validation, control the vehicle according to the input. Based on a determination that the vehicle has navigated the scenario, the guidance system may release vehicle guidance back to the vehicle computing system.

Abstract: Techniques are discussed for modifying map elements associated with map data. Map data can include three-dimensional data (e.g., LIDAR data) representing an environment, while map elements can be associated with the map data to identify locations and semantic information associated with an environment, such as regions that correspond to driving lanes or crosswalks. A trajectory associated with the map data can be updated, such as when aligning one or more trajectories in response to a loop closure, updated calibration, etc. The transformation between a trajectory and an updated trajectory can be applied to map elements to warp the map elements so that they correspond to the updated map data, thereby providing automatic and accurate techniques for updating map elements associated with map data.

Abstract: A sensor pod system includes one or more sensor pods with a plurality of sensors configured to collect data from an environment. The sensor pod system may include a cleaning system to clean sensing surfaces of sensor pods during operation. The sensor pod system may include sensors of different types and modalities. Sensor pods of the sensor pod system may be modularly installed on a vehicle, for example, an autonomous vehicle and collect and provide data of the environment during operation of the vehicle.

Abstract: A method and system of determining whether a stationary vehicle is a blocking vehicle to improve control of an autonomous vehicle. A perception engine may detect a stationary vehicle in an environment of the autonomous vehicle from sensor data received by the autonomous vehicle. Responsive to this detection, the perception engine may determine feature values of the environment of the vehicle from sensor data (e.g., features of the stationary vehicle, other object(s), the environment itself). The autonomous vehicle may input these feature values into a machine-learning model to determine a probability that the stationary vehicle is a blocking vehicle and use the probability to generate a trajectory to control motion of the autonomous vehicle.

Abstract: Techniques for determining map data for localizing a vehicle in an environment are discussed herein. A vehicle can capture sensor data such as image data and can detect objects in the sensor data. Detected objects can include semantic object such as traffic lights, lane lines, street signs, poles, and the like. Rays based on a pose of the sensor and the detected objects can be determined. Intersections between the rays can be determined. The intersections can be utilized to determine candidate landmarks in the environment. The candidate landmarks can be utilized to determine landmarks and to eliminate other candidate landmarks. The map data can be determined based on the three-dimensional locations and utilized to localize vehicles.

Abstract: Acceleration determination for controlling a vehicle, such as an autonomous vehicle, is described. In an example, objects in an environment of the vehicle are identified and a probability that each object will impact travel of the vehicle is determined. Individual accelerations for responding to each object may also be determined. Weighting factors for each of the accelerations may also be determined based on the probabilities. A control acceleration may be determined based on the weighting factors and the accelerations.

Abstract: A safety system for vehicle may include a restraint surface adjustment mechanism for adjusting at least one of a height or an angle of a restraint surface disposed under a vehicle seat during a collision and/or predicted collision in which the vehicle seat is facing in the direction of travel and/or the direction of the oncoming collision. The seat may comprise a bench seat including a first seating space and a second seating space. A first restraint surface adjustment mechanism may be associated with the first seating space and a second restraint surface adjustment mechanism may be associated with the second seating space. The restraint surface adjustment mechanism may include, for example, an inflatable bladder, a movable plate which rotates about an axis, or other restraint surface adjustment mechanisms that adjust at least one of the height, angle, or physical property (e.g., rigidity) of one or more restraint surfaces.

Abstract: Techniques and methods for testing a structural integrity of a vehicle. For instance, the vehicle may use suspension(s) to lift corners of the vehicle, where lifting the corners creates a torsion force in the body of the vehicle. The vehicle may then use sensor(s) to determine a deflection that is caused by the torsion force. Next, the vehicle may determine a stiffness associated with the body of the vehicle using the force that was applied to lift the corners and the deflection. After determining the stiffness, the vehicle may compare the stiffness to a baseline stiffness in order to determine whether there is a problem with the structural integrity of the vehicle. The baseline stiffness may include s standard stiffness or be based on a previous test of the vehicle. If the vehicle determines that there is no problem, then the vehicle may continue to operate as intended.

Abstract: Energy consumption for a vehicle may be reduced based at least in part on an environment characteristic associated with the environment through which the vehicle travels or an operation characteristic associated with operation of the vehicle, thereby increasing an operational time of the vehicle. In some situations, reducing energy consumption may be associated with operation of one or more of a sensor (e.g., turning the sensor off, reducing a frequency or resolution of the sensor, etc.) and/or one or more processors associated with the vehicle (e.g., turning a processor off, reducing a rate of computation, etc.) based at least in part on one or more of the environment characteristic signal or the operation characteristic signal.

Abstract: A LIDAR system includes a laser emitter configured to emit a laser pulse in a sample direction of a sample area of a scene. A sensor element of the LIDAR system is configured to sense a return pulse, which is a reflection from the sample area corresponding to the emitted laser pulse. The LIDAR system may compare a width of the emitted laser pulse to a width of the return pulse in the time-domain. The comparison of the width of the emitted pulse to the width of the return pulse may be used to determine an orientation or surface normal of the sample area relative to the sample direction. Such a comparison leads to a measurement of the change of pulse width, referred to as pulse broadening or pulse stretching, from the emitted pulse to the return pulse.

Abstract: Techniques for presenting a user interface on a display for monitoring and/or controlling a vehicle. The user interface may include a digital representation of an environment in which the vehicle is operation. Additionally, the user interface may include system interface that is configured to display one or more notifications associated with systems or components of the vehicle. The system interface may additionally, or alternatively, comprise one or more control inputs for controlling systems or components of the vehicle. The user interface may also include a mission interface that includes a map interface and a mission selection interface for selecting routes the vehicle is to navigate. The user interface may additionally cause presentation of visual indicators that indicate the presence of an object that is not shown on the user interface, but that is moving in a direction such that the object will soon be visibly displayed on the user interface.

Abstract: A vehicle can use an image sensor to both detect objects and determine depth data associated with the environment the vehicle is traversing. The vehicle can capture image data and lidar data using the various sensors. The image data can be provided to a machine-learned model trained to output depth data of an environment. Such models may be trained, for example, by using lidar data and/or three-dimensional map data associated with a region in which training images and/or lidar data were captured as ground truth data. The autonomous vehicle can further process the depth data and generate additional data including localization data, three-dimensional bounding boxes, and relative depth data and use the depth data and/or the additional data to autonomously traverse the environment, provide calibration/validation for vehicle sensors, and the like.

Abstract: Operations associated with charging a vehicle may generate thermal energy. A passive thermal management solution may dissipate the thermal energy without requiring additional active components and without adding significant thermal loads to an existing thermal management system. In some examples, a passive heat exchanger may include a cold plate coupled to power electronics. In addition, the passive heat exchanger may include a condenser that is fluidly coupled to the cold plate and is positioned in an airflow path.

Abstract: Techniques for using a set of non-steering variables to estimate an angle of a wheel are described. For example, a yaw rate, a linear velocity of a wheel, and vehicle dimensions (e.g., offset between the wheel and a turn-center reference line), can be used to estimate the angle of the wheel. Among other things, estimating angles based on non-steering variables may provide redundancy (e.g., when determined in parallel with steering-based command angles or other commanded angles) and/or may be used to validate commanded angles based on steering components.

Abstract: Techniques for determining a speed for a vehicle as it traverses an environment with pedestrians are discussed herein. For example, a vehicle computing system may implement techniques to determine an action for a vehicle to take based on a detected pedestrian in an environment. The vehicle computing system may receive sensor data of an environment from a sensor associated with a vehicle, determine, based at least in part on the sensor data, an object in the environment and receive a predicted object trajectory associated with the object. The vehicle computing system may then determine, based on the predicted object trajectory, a distance between a simulated vehicle passing location and a predicted object location, determine, based on the distance, a speed, determine, based on the distance and the speed, a trajectory for the vehicle to follow, and control the vehicle based on the trajectory.

Abstract: Fast simulation of a scenario (e.g., simulating the scenario once as opposed to multiple times) to determine performance metric(s) of a configuration of one or more components of an autonomous vehicle may include training a perception error model based at least in part on a difference between a prediction output by a perception component associated with a future time and a perception output associated with that future time once that future time has arrived. A contour or heat map output by the perception error model may be used to determine one or more performance metric(s) associated with a component of the autonomous vehicle and identify which component may cause a degradation of a performance metric.