Abstract: An occupant protection system for a vehicle may include an expandable curtain and/or an expandable bladder configured to be expanded from a stowed state to a deployed state. The system may also include a transverse ceiling trim panel and one or more side ceiling trim panels configured to be coupled to a ceiling of the vehicle, with the transverse ceiling trim panel extending substantially transversely with respect to the one or more side ceiling trim panels. Portions of the ceiling trim panels may be configured to deflect and allow expansion of the expandable curtain and/or the expandable bladder to the deployed state. The system may also include a deployment controller and one or more inflators configured to cause deployment of the expandable curtain at a first time and deployment of the expandable bladder at a second time after the first time.

Abstract: A sensor pod system includes one or more sensor pods with a plurality of sensors configured to collect data from an environment. A sensor pod may have an effective field of view created by individual sensors with overlapping fields of view. The sensor pod system may include sensors of different types and modalities. Sensor pods of the sensor pod system may be modularly disposed on a vehicle, for example, an autonomous vehicle to collect and provide data of the environment during operation of the vehicle. The sensor pods may be disposed at elevated locations around the vehicle to reduce obstacles within the sensor pods fields of view.

Abstract: Motion can be induced at a vehicle, e.g., by actuating components of an active suspension system, and first sensor data and second sensor data representing an environment of the vehicle can be captured at a first position and a second position, respectively, resulting from the induced motion. A second sensor can determine motion information associated with the first position and the second position. Calibration information about the sensor, the first sensor data, and the motion information can be used to determine an expectation of sensor data at the second position. A calibration error can be the difference between the second sensor data and the expected sensor data.

Abstract: Techniques for determining a safety metric associated with a vehicle controller are discussed herein. To determine whether a complex system (which may be uninspectable) is able to operate safely, various operating regimes (scenarios) can be identified based on operating data and associated with a scenario parameter to be adjusted. To validate safe operation of such a system, a scenario may be identified for inspection. Error metrics of a subsystem of the system can be quantified. The error metrics, in addition to stochastic errors of other systems/subsystems can be introduced to the scenario. The scenario parameter may also be perturbed. Any multitude of such perturbations can be instantiated in a simulation to test, for example, a vehicle controller. A safety metric associated with the vehicle controller can be determined based on the simulation, as well as causes for any failures.

Abstract: A seat for a vehicle may include a seatback including one or more inflatable bladders that may be configured to provide adjustable lumbar support and to deploy in response to a triggering event signal indicative of a change of velocity, collision, or predicted collision event. One or more inflatable bladders may be configured to be independently controllable and configured to provide adjustable lumbar support at a region of the seatback during normal vehicle operation. Moreover, when at least a portion of the back of an occupant of the seat pushes against a front surface of the seatback due to the event, the one or more inflatable bladders may be configured to compress at least partially a comfort foam or comfort material in the seatback and expedite engagement of the energy absorbing material with the occupant's back.

Abstract: A door interface system for a vehicle door includes a sensor and a visual indicator. The sensor may be a proximity sensor and may be positioned proximate to the visual indicator such that it will detect an object proximate to the proximity sensor. The visual indicator may convey the position of the sensor and/or a status of the vehicle door. The door interface system is configured to control the vehicle door based at least in part on detecting an object proximate the visual indicator.

Abstract: Techniques for determining information associated with sounds detected in an environment based on audio data and map data or perception data are discussed herein. A vehicle can use map data and/or perception data to distinguish between multiple audio signals or sounds. A direct source of sound can be distinguished from a reflected source of sound by determining a direction of arrival of sounds and which objects the directions of arrival are associated with in the environment. A reflected sound can be received without receiving a direct sound. Based on the reflected sound and map data or perception data, characteristics of sound in an occluded region of the environment may be determined and used to control the vehicle.

Abstract: Techniques for diagnosing and disambiguating a bias in one or more axels of a bidirectional four-wheel drive vehicle. In some examples, the diagnostics system may diagnose and disambiguate the bias in the two axles by collecting data related to the movement of the vehicle while the vehicle traverses a zero curvature path in a forward direction. The diagnostics system may then determine a bias in an axle acting as the rear axle based on the collected data. The bias in the axle acting as the front axle may then be determined based on the collected data and the bias in the rear axle.

Abstract: Techniques for controlling a vehicle based on height data and/or classification data being determined utilizing multi-channel image data are discussed herein. The vehicle can capture lidar data as it traverses an environment. The lidar data can be associated with a voxel space as three-dimensional data. Semantic information can be determined and associated with the lidar data and/or the three-dimensional voxel space. A multi-channel input image can be determined based on the three-dimensional voxel space and input into a machine learned (ML) model. The ML model can output data to determine height data and/or classification data associated with a ground surface of the environment. The height data and/or classification data can be utilized to determine a mesh associated with the ground surface. The mesh can be used to control the vehicle and/or determine additional objects proximate the vehicle.

Abstract: Techniques relating to multi-passenger interaction via display(s) of a vehicle are described. In an example, sensor data is received from a sensor associated with an interior of a vehicle. Based at least partly on the sensor data, a first occupancy state associated with a first seat of the vehicle and a second occupancy state associated with a second seat of the vehicle can be determined. Content to present via displays associated with the first seat and/or the second seat can be determined based at least in part on the first occupancy state and the second occupancy state and can be presented via each respective display.

Abstract: A vehicle can include various sensors to detect objects in an environment. Sensor data can be captured by a perception system in a vehicle and represented in a voxel space. Operations may include analyzing the data from a top-down perspective. From this perspective, techniques can associate and generate masks that represent objects in the voxel space. Through manipulation of the regions of the masks, the sensor data and/or voxels associated with the masks can be clustered or otherwise grouped to segment data associated with the objects.

Abstract: A lidar photosensor amplification circuit may include light sensors; amplifiers corresponding respectively to the light sensors, in a powered-on state, to amplify output signals of the respective light sensors as amplified outputs; and switches corresponding respectively to the amplifiers, where individual switches may be controlled to pass a respective amplified output in a closed state or disconnect the amplified output in an open state. The lidar photosensor amplification circuit may be controlled by a controller according to timing rules that conserve power supplied to photosensor amplification circuit, reduce heat produced by the light sensor board, and do not aggravate cross-talk between sensors. The timing rules include staging an amplifier for a staging time before the corresponding light sensor is to be read, closing a switch after the staging time has passed, and powering down the amplifier and opening the switch after a reading time passes.

Abstract: Techniques described herein are directed to comparing, using a machine-trained model, neural network activations associated with data representing a simulated environment and activations associated with data representing real environment to determine whether the simulated environment is causes similar responses by the neural network, e.g., a detector. If the simulated environment and the real environment do not activate the same way (e.g., the variation between neural network activations of real and simulated data meets or exceeds a threshold), techniques described herein are directed to modifying parameters of the simulated environment to generate a modified simulated environment that more closely resembles the real environment.

Abstract: Techniques for estimating a height range of an object in an environment are discussed herein. For example, a sensor, such as a lidar sensor, can capture three-dimensional data of an environment. The sensor data can be associated with a two-dimensional representation. A ground surface can be removed from the sensor data, and clustering techniques can be used to cluster remaining sensor data provided in a two-dimensional representation to determine object(s) represented therein. A height of a sensor object can be represented as a first height based on an extent of the sensor data associated with the object and can be represented as a second height based on beam spreading aspects of the sensor data and/or sensor data associated with additional objects. Thus, a minimum and/or maximum height of an object can be determined in a robust manner. Such height ranges can be used to control an autonomous vehicle.

Abstract: A reflector unit may behave as a retroreflector to reflect light of a selected color. The reflector unit may comprise a first reflector having a first color, a second reflector having a second color, and a mask that either allows incoming light to reach the first reflector and not the second reflector or allows incoming light to reach the second reflector and not the first reflector. An active light unit may emit light of a particular color in response to receiving light. In this fashion, the active light unit may simulate the operation of a reflector. The reflector unit and the active light unit may operate on a bi-directional vehicle.

Abstract: Using detection of low variance regions for improving detection is described. In an example, sensor data can be received from a sensor associated with a vehicle. The sensor data can represent an environment. An indication of a low variance region associated with the sensor data can be determined and an indication of a high variance region associated with the sensor data can be determined based at least in part on the indication of the low variance region. The vehicle can be controlled based on at least one of the sensor data or the indication of the high variance region.

Abstract: Some radar sensors may provide a Doppler measurement indicating a relative velocity of an object to a velocity of the radar sensor. Techniques for determining a two-or-more-dimensional velocity from one or more radar measurements associated with an object may comprise determining a data structure that comprises a yaw assumption and a set of weights to tune the influence of the yaw assumption. Determining the two-or-more-dimensional velocity may further comprise using the data structure as part of regression algorithm to determine a velocity and/or yaw rate associated with the object.

Abstract: A thermal management system may cool at least a portion of a computer system with one or more cooling systems. The thermal management system can include one or more modular heatsink assemblies. The modular heatsink assemblies can include scalable heat spreader panels that are thermally coupled to a portion of the one or more cooling systems. The modular heatsink assembly can be positioned above and/or adjacent to a computer component, such as a dual in-line memory module. The scalable heat spreader panels are shaped to fit in between and to the sides of the computing component to draw heat away from the computing component.

Abstract: Demand associated with one or more vehicle systems can be predicted for a vehicle traversing a planned travel path. Based at least in part on the predicted demand, a control strategy can be determined for controlling operation of the one or more vehicle systems to optimize for efficiency, cabin temperature, component temperature, passenger comfort, etc. The one or more vehicle systems can be controlled, based at least in part on the control strategy, at least one of before the vehicle traverses the travel path, or as the vehicle traverses the travel path.