Abstract: Techniques relating to performance-based metrics for evaluating system quality are described. In an example, sensor data associated with an environment within which a vehicle is positioned is received. A performance metric associated with a trajectory, indicative of a performed behavior of the vehicle, can be determined and a correctness metric can be determined based at least in part on the performance metric. The correctness metric can represent a correctness of the performed behavior. Modification(s) to component(s) and/or system(s), or portions thereof, of the vehicle can be affected based at least in part on the correctness metric.

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. In the deployed state, the expandable curtain may include first and second sides configured to extend along respective portions of first and second interior sides of the vehicle. The expandable curtain may also include a transverse portion extending between the first and second sides, and the first and second sides, and the transverse portion of the expandable curtain may form a contiguous barrier. The expandable bladder when deployed may be supported by the expandable curtain during contact by an occupant. The occupant protection system may also include a deployment control system configured to cause the expandable curtain and/or the expandable bladder to expand to the deployed state. The occupant protection system may be used in vehicles having a carriage-style seating arrangement.

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 installed on a vehicle, for example, an autonomous vehicle and collect and provide data of the environment during operation of the vehicle.

Abstract: Driving simulations may be generated based on driving log data and used to validate autonomous vehicle safety systems. A driving simulation system may receive driving log data from autonomous vehicles and determine events which caused a vehicle to diverge from a planned trajectory. Driving simulations may be generated based on the driving log data, and executed using a simulated vehicle that follows the initial planned trajectory of the autonomous vehicle. The driving simulations may be analyzed to detect potential collisions and near misses, and to determine success conditions for the behaviors of vehicle safety systems. Driving simulations and associated success conditions may be aggregated and used in validation suites for vehicle controllers and/or vehicle safety systems, thereby providing more comprehensive and robust autonomous vehicle validation based on real-world driving scenarios.

Abstract: This disclosure describes techniques for detecting multipath radar returns and modifying radar data. A vehicle may use radar devices to receive radar data while traversing within an environment. The vehicle may process the radar data using a virtual array based on an arraignment of the antennae within an aperture of the radar device. Using the virtual array, the vehicle may determine an elevated noise level that may be indicative of a multipath radar return. Based on the elevated noise level, the vehicle may determine a second virtual array associated with multipath radar returns, and may process the radar data using the second virtual array. Based on determining that the noise level associated with the second virtual array is lower than the initial noise level, the vehicle may determine that the radar data includes a multipath radar return, and may modify the radar data to correct or mitigate the error caused by the multipath return.

Abstract: Sensors, including time-of-flight sensors, may be used to detect objects in an environment. In an example, a vehicle may include a time-of-flight sensor that images objects around the vehicle, e.g., so the vehicle can navigate relative to the objects. Sensor data generated by the time-of-flight sensor can include returns associated with highly reflective objects that cause glare. In some examples, a depth of a sensed surface is determined from the sensor data and additional pixels at the same depth are identified. The subset of pixels at the depth are filtered by comparing a measured intensity value to a threshold intensity value for the depth. Other threshold intensity values can be applied to subsets of pixels at different depths.

Abstract: Techniques for representing sensor data and predicted behavior of various objects in an environment are described herein. For example, an autonomous vehicle can represent prediction probabilities as an uncertainty model that may be used to detect potential collisions, define a safe operational zone or drivable area, and to make operational decisions in a computationally efficient manner. The uncertainty model may represent a probability that regions within the environment are occupied using a heat map type approach in which various intensities of the heat map represent a likelihood of a corresponding physical region being occupied at a given point in time.

Abstract: Vehicles may be associated with a variety of different types of events, including events associated with vehicle operations and/or events associated with vehicle passengers. The present disclosure is related to, when an event is detected, exchanging information with a vehicle passenger, such as via the passenger's mobile device and/or wearable device. In some instances, an event may be detected, and examples of the present disclosure may provide an application notification presenting various information. The notification may, in some examples, be configured to help the passenger locate the passenger device, to alert the passenger to the event, to provide instructions, and/or to provide a control interface for controlling a vehicle operation. In some examples, the notification may supersede operations of the passenger device, such as by being presented even if the device is in a locked state or has an unrelated application open and in the foreground.

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 include a housing and extend from a portion of a body of a vehicle. The sensor pod housing may have energy absorbing structures configured to absorb and dissipate energy during an impact in order to protect a pedestrian.

Abstract: Validating a component of an autonomous vehicle may comprise determining, via simulation, a likelihood that operation of the component will result in an adverse event. Such simulations may be based on log data developed from real world driving events to, for example, accurately model a likelihood that a scenario will occur during real-world driving. Because adverse events may be exceedingly rare, the techniques may include modifying a probability distribution associated the likelihood that a scenario is simulated, determining a metric associated with an adverse event (e.g., a likelihood that operating the vehicle or updating a component thereof will result in an adverse event), and applying a correction to the metric based on the modification to the probability distribution.

Abstract: Techniques for validating operation of a perception system that is configured to detect objects in an environment of a vehicle are described herein. The techniques may include receiving log data representing a real scenario in which the vehicle was traversing an environment. Based at least in part on the log data, an error may be identified that is associated with an output received from the perception system while the vehicle was traversing the environment. In some examples, a determination may be made that a magnitude of the error violates a perception system requirement, the requirement established based on a determination that the magnitude of the error would contribute to an adverse event in an alternative scenario. Based on the magnitude of the error contributing to the adverse event, data associated with the error may be output for use in updating the perception system to at least meet the requirement.

Abstract: A seat for a vehicle may include a seatback including a variable resistance support disposed within a volume of the seatback. The variable resistance support may further include one or more configurable arrays of resistive elements including collapsible structures and/or inflatable bladders that may be configured to provide energy dissipation and/or absorption during a collision event. One or more array subsets may be configured to be independently controllable and configured to provide adjustable support at a region of the seatback, the adjustable support corresponding to a mass of the occupant. Moreover, when at least a portion of the back of an occupant pushes against a front surface of the seatback due to the collision event, the arrays of resistive elements may be configured to compress and/or collapse, at least partially, to absorb an energy applied from an occupant's back associated with the collision event.

Abstract: Techniques for verification of interchangeable connectors are disclosed which include applying one or more identification tags to connectors. The identification tags have identifiers which may be associated with one another for connectors that correspond. The identifiers may be read from the identification tags when the connectors are connected to determine if the connected connectors are associated.

Abstract: An occupant constraint system may include a belt marker on a seat belt in a passenger compartment of the vehicle for restraining a passenger during a collision. The occupant constraint system may include a camera system for producing marker position data that is indicative of a position of the marker, and a physical characteristic estimator that is uses the marker position data to produce a physical characteristic estimate of a physical characteristic estimate of the passenger. The occupant constraint system may include a passenger related system having a passenger function and the passenger related system may control the passenger function based at least in part on the physical characteristic estimate.

Abstract: An active suspension control system for a vehicle includes a mathematical model based on a modal expansion of the vehicle. Model parameters of the vehicle can be extracted from the modal expansion using sensor data generated on the vehicle, e.g., on demand and/or in real time. The model parameters and the modal expansion can be used to determine a vehicle state, predict future vehicle states, and control aspects of an active suspension system based on the predicted future vehicle states. The model parameters may also be used to update the mathematical model, e.g., to account for component wear over time, and/or to detect anomalies or defects in the active suspension system.

Abstract: Techniques for receiving and processing sensor data captured by a fleet of vehicle are discussed herein. In some examples, a fleet dashcam system can receive sensor data captured by electronic devices on a fleet of vehicles and can use that data to detect collision and near-collision events. The data of the collision or near-collision event can be used to determine a simulation scenario and a response of an autonomous vehicle control to the simulation scenario and/or it can be used to create a collision heat map to aid in operation of an autonomous vehicle.

Abstract: Four-wheel steering of a vehicle, e.g., in which leading wheels and trailing wheels are steered independently of each other, can provide improved maneuverability and stability. Steering angle constraints may be used to limit or prevent saturation of steering by only one set of wheels as well as to reduce sideslip. The steering angle constraints are vehicle independent and applicable across a fleet of different vehicles based on vehicle speed. For instance, the steering angle constraints establish angle limits that dynamically adjust based on vehicle speed to ensure vehicle velocity and acceleration remain within predefined limits as established by autonomous vehicle system design.