Abstract: A vehicle safety system of a vehicle facilitates safe exigency ingress into a vehicle. The vehicle safety system may receive data associated with a condition of the vehicle (e.g., from sensors, components, remote signals, passenger input, etc.). Based at least in part on the data associated with the condition of the vehicle, the vehicle safety system may detect a triggering event associated with the ingress of a passenger compartment of the vehicle. Based at least in part on the triggering event, the vehicle safety system may perform a vehicular safety measure associated with ingress to the passenger compartment of the vehicle.

Abstract: Depth estimates for an object made by one or more sensors of a vehicle may be refined using locations of environmental attributes that are proximate the object. An image captured of the object proximate an environmental attribute may be analyzed to determine where the object is positioned relative to the environmental attribute. A machine-learned model may be used to detect the environmental attribute, and a location of the environmental attribute may be determined from map data. A probability of a location of the object may be determined based on the known location of the environmental attribute. The location probability of the object may be used to refine depth estimates generated by other means, such as a monocular depth estimation from an image using computer vision.

Abstract: A system for charging a battery carried by a vehicle may include a charging box for coupling to a vehicle chassis and including interface electrical contacts electrically coupled to the battery. The system may also include a charge coupler including coupler electrical contacts for electrically coupling to the interface electrical contacts from under the vehicle and configured to be coupled to an electrical power supply. The charging box may include an interface activation surface, and the charge coupler may include a housing for enclosing the coupler electrical contacts and including a base for supporting the coupler electrical contacts, a coupler activation surface opposite the base, an opening, and a door configured to open the opening to expose the coupler electrical contacts as the interface activation surface contacts the coupler activation surface and moves the coupler activation surface toward the base.

Abstract: Techniques for determining that a first vehicle is associated with a reverse state, and controlling a second vehicle based on the reverse state, are described herein. In some examples, the first vehicle may provide an indication that the first vehicle will be executing a reverse maneuver, such as with reverse lights on the vehicle or by positioning at an angle relative to a road or parking space to allow for the reverse maneuver into a desired location. A planning system of the second vehicle (such as an autonomous vehicle) may receive sensor data and determine a variety of these indications to determine a probability that the vehicle is going to execute a reverse maneuver. The second vehicle can further determine a likely trajectory of the reverse maneuver and can provide appropriate accommodations (e.g., time and/or space) to allow the second vehicle to execute the maneuver safely and efficiently.

Abstract: Techniques for training a machine learned (ML) model to determine depth data based on image data are discussed herein. Training can use stereo image data and depth data (e.g., lidar data). A first (e.g., left) image can be input to a ML model, which can output predicted disparity and/or depth data. The predicted disparity data can be used with second image data (e.g., a right image) to reconstruct the first image. Differences between the first and reconstructed images can be used to determine a loss. Losses may include pixel, smoothing, structural similarity, and/or consistency losses. Further, differences between the depth data and the predicted depth data and/or differences between the predicted disparity data and the predicted depth data can be determined, and the ML model can be trained based on the various losses. Thus, the techniques can use self-supervised training and supervised training to train a ML model.

Abstract: Techniques for, among other things, detecting faults associated with inertial measurement units (IMUs) of a vehicle when multiple IMUs are coupled to the vehicle are described herein. The techniques may include receiving first data from a first IMU of the vehicle and receiving second data from a second IMU of the vehicle. Based at least in part on the first data and the second data, a rotation of the first IMU relative to the second IMU may be calculated. The calculated rotation between the first IMU and the second IMU may be indicative of a fault associated with the first IMU or the second IMU. In response to detecting the fault, an action may be performed with respect to the first IMU or the second IMU to correct for the fault.

Abstract: A time delay of arrival (TDOA) between a time that a light pulse was emitted to a time that a pulse reflected off an object was received at a light sensor may be determined for saturated signals by using an edge of the saturated signal, rather than a peak of the signal, for the TDOA calculation. The edge of the saturated signal may be accurately estimated by fitting a first polynomial curve to data points of the saturated signal, defining an intermediate magnitude threshold based on the polynomial curve, fitting a second polynomial curve to data points near an intersection of the first polynomial curve and the intermediate threshold, and identifying an intersection of the second polynomial curve and the intermediate threshold as the rising edge of the saturated signal.

Abstract: Techniques for providing a user interface for remote vehicle monitoring and/or control include presenting a digital representation of an environment and a vehicle as it traverses the environment on a first portion of a display and presenting on a second portion of the display a communication interface that is configured to provide communication with multiple people. The communication interface may enable communications between a remote operator and any number of occupants of the vehicle, other operators (e.g., other remote operators or in-vehicle operators), and/or people in an environment around the vehicle. The user interface may additionally include controls to adjust components of the vehicle, and the controls may be presented on a third portion of the display. Furthermore, the user interface may include a vehicle status interface that provides information associated with a current state of the vehicle.

Abstract: A suspension system for controlling movement of a vehicle wheel may include a spring and damper assembly coupling the wheel to the vehicle chassis for movement of the wheel relative to the vehicle chassis. The spring and damper assembly may include a spring coupled to a damper member configured to extend and retract the wheel relative to the vehicle chassis. The suspension system may further include a damper actuator located remotely from the spring and damper assembly and configured to modify an amount of damping and/or wheel extension. The suspension system may also include a spring actuator integrated with the damper actuator and configured to control an amount of deflection of the spring and/or to alter a spring rate. The damper actuator may be provided at a location in the vehicle separated from the spring and damper assembly.

Abstract: Techniques and methods for determining a distance between a point within an environment and a reference line are discussed herein. For instance, a vehicle may be navigating. While navigating, the vehicle may receive a reference line that represents a road segment and determine various regions relative to the reference line. Additionally, the vehicle may generate sensor data representing the environment and identify an object using the sensor data. The vehicle may then determine that a location of the object corresponds to a region from the regions. Based on the region, the vehicle may determine a rule for identifying the distance between the vehicle and the reference line. The vehicle may then determine the distance using the rule, the location of the object, and the reference line. Additionally, the vehicle may determine an action for the vehicle to perform that is based on the distance.

Abstract: Tracking a current and/or previous position, velocity, acceleration, and/or heading of an object using sensor data may comprise determining whether to associate a current object detection generated from recently received (e.g., current) sensor data with a previous object detection generated from formerly received sensor data. In other words, a track may identify that an object detected in former sensor data is the same object detected in current sensor data. However, multiple types of sensor data may be used to detect objects and some objects may not be detected by different sensor types or may be detected differently, which may confound attempts to track an object. An ML model may be trained to receive outputs associated with different sensor types and/or a track associated with an object, and determine a data structure comprising a region of interest, object classification, and/or a pose associated with the object.

Abstract: Aspects of the invention relate to a method comprising: determining an output torque at a wheel of a vehicle mounted to a test apparatus comprising an external motor, the output torque being in response to a command; determining a correction factor based on the output torque and at least one coefficient associated with a reaction of a component of the vehicle and/or of the test apparatus to an applied torque at the vehicle; and controlling the external motor to apply the correction factor to the wheel of the vehicle.

Abstract: A thermal management assembly may implement cooling techniques to cool at least a portion of a computer system with one or more cooling systems. The techniques may include using a thermal management assembly in fluid communication with the cooling system(s) to supply fluid from at least one of the cooling systems to at least a portion of the computer system. The techniques may also or instead include using a first thermal coupling to transfer thermal energy between the first cooling system and the computer system and a second thermal coupling to transfer thermal energy between the second cooling system and the computer system. Cooling a computer system using the cooling techniques described herein lowers an operating temperature of the computer system thereby mitigating heat related computer failure.

Abstract: A method for operating a fleet of vehicles may include determining a first set of parameters for operating a first vehicle as it travels to a destination, and determining a second set of parameters for operating a second vehicle. Consumption of the first set of parameters by the first vehicle may cause the first vehicle to accelerate, alter shocks and/or suspensions, and/or move into a free lane. Consumption of the second set of parameters by the second vehicle may cause the second vehicle to remain outside of a drive envelope of the first vehicle, between the first vehicle and the particular destination.

Abstract: This disclosure is directed to calibrating sensors for an autonomous vehicle. First sensor data and second sensor data can be captured by one or more sensors representing an environment. The first sensor data and the second sensor data can be associated with a grid in a plurality of combinations to generate a plurality of projected data. A number of data points of the projected data occupying a cell of the grid can be summed to determine a spatial histogram. An amount of error (such as an entropy value) can be determined for each of the projected data, and the projected data corresponding to the lowest entropy value can be selected as representing a calibrated configuration of the one or more sensors. Calibration data associated with the lowest entropy value can be determined and used to calibrate the one or more sensors, respectively.

Abstract: An electronic braking system with independent antilock braking and stability control. The system can utilize a variety of electro-mechanical actuators to apply clamping force to a mechanical brake caliper. The system can include a caliper electronic control unit (CECU) and a wheel speed sensor at each wheel of the vehicle to enable independent slip control, or antilock braking, at each wheel. A separate executive management unit (EMU) can receive data from each electronic caliper, vehicle accelerometers, and other sensors to provide electronic stability control (ESC) independent of antilock braking (ABS) functions. The removal of a conventional master cylinder, brake pedal, ABS pump, brake lines, and other components can reduce weight and complexity. The elimination of hydraulic lines running to a central ABS module and master cylinder can enable modular drive units to be swapped out more quickly and efficiently.

Abstract: Techniques associated with generating and maintaining sparse geographic and map data. In some cases, the system may maintain a factor graph comprising a plurality of nodes. In some cases, the nodes may comprise pose data and sensor data associated with an autonomous vehicle at the geographic position represented by the node. The nodes may be linked based on shared trajectories and shared sensor data.

Abstract: Techniques and methods for performing collision monitoring using system data. For instance, a vehicle may generate sensor data using one or more sensors. The vehicle may then analyze the sensor data using systems in order to determine parameters associated with the vehicle and parameters associated with another object. Additionally, the vehicle may determine uncertainties associated with the parameters and then process the parameters using the uncertainties. Based at least in part on the processing, the vehicle may determine a distribution of estimated locations associated with the vehicle and a distribution of estimated locations associated with the object. Using the distributions of estimated locations, the vehicle may determine the probability of collision between the vehicle and the object.

Abstract: A seat for a vehicle includes an occupant protection system. The occupant protection system includes an airbag or other barrier that at least partially occludes an opening to a volume under a vehicle seat. The occupant protection system may reduce or prevent lower leg injury and/or retain cargo in the volume during a collision event.

Abstract: Techniques for predicting safety metrics associated with near-miss conditions for a vehicle, such as an autonomous vehicle, are discussed herein. For instance, a training system identifies an object in an environment and determines a trajectory for the object. The training system may receive a trajectory for a vehicle and associate the trajectory for the object and the trajectory for the vehicle with an event involving the object and the vehicle. In examples, the training system determines a parameter associated with motion of the vehicle as indicated by the trajectory of the vehicle relative to the trajectory of the object, and the event. Then, the training system may determine a safety metric associated with the event that indicates whether the vehicle came within a threshold of a collision with the object during a time period associated with the event.