Methods and systems for monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, operating data may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include actions the feature would have taken to control the vehicle, but which were not taken because a vehicle operator was controlling the relevant aspect of vehicle operation at the time. The operating data may be recorded in a log, which may then be used to determine risk levels associated with vehicle operation based upon risk levels associated with the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.

A vehicle computing system may implement techniques to predict behavior of objects detected by a vehicle operating in the environment. The techniques may include determining a feature with respect to a detected objects (e.g., likelihood that the detected object will impact operation of the vehicle) and/or a location of the vehicle and determining based on the feature a model to use to predict behavior (e.g., estimated states) of proximate objects (e.g., the detected object). The model may be configured to use one or more algorithms, classifiers, and/or computational resources to predict the behavior. Different models may be used to predict behavior of different objects and/or regions in the environment. Each model may receive sensor data as an input, and output predicted behavior for the detected object. Based on the predicted behavior of the object, a vehicle computing system may control operation of the vehicle.

A system for automated flight correction is an electric aircraft that includes an input control configured to receive a user input and generate a control datum as a function of the user input, at least a sensor connected to the electric aircraft that is configured to detect a status datum and transmit the status datum to a flight controller, a flight controller communicatively connected to the input control and the at least a sensor configured to receive the control datum from the input control, receive the status datum from the flight controller and determine a command datum as a function of the control datum and status datum, and an actuator connected to the flight controller configured to receive the command datum from the flight controller and command at least a flight component as a function of the command datum.

Described herein are methods of generating learning data to facilitate de-biasing the labeled location of an object of interest within an image. Methods may include: receiving sensor data, where the sensor data is a first image; determining reference corner locations of an object in the first image using image processing; generating observed corner locations of the object in the first image from the determined reference corner locations; generating a bias transformation based, at least in part, on a difference between the reference corner locations and the observed corner locations of the object in the first image; receiving sensor data from another image sensor of a second image; receiving observed corner locations of an object in the second image from a user; and applying the bias transformation to the observed corner locations of the object in the second image to generate de-biased corners for the object in the second image.

Systems and methods are provided for influential control over a driver's hand(s) that grip a vehicle's steering wheel. Upon issuing an autonomous control signal to control motive operation of the vehicle, an autonomous control system of the vehicle may further reinforce the application of the autonomous control signal by inducing the driver's hand(s) to grip/increase grip strength on the vehicle's steering wheel or by releasing the grip/decreasing grip strength on the vehicle's steering wheel. Moreover, the increasing/decreasing of the driver's grip may alternatively, or in addition to the reinforcement aspect, induce augmentative or intervening action(s)/behavior(s) by the driver.

A one-touch control system for operating the controls of a towed vehicle using a towing vehicle. The system includes an electronic control unit integrated into the towed vehicle and configured to receive a selection signal from the towing vehicle and simultaneously control a number of different components based on the selection signal. The components including a switch configured to turn on and off the towed vehicle, a sensor configured to detect whether a passenger is present in the towed vehicle, and an odometer configured to be deactivated when the switch indicates that the towed vehicle is off and the sensor indicates that there are no passengers in the towed vehicle.

Systems and vehicle are provided. A vehicle system for a vehicle includes: a trajectory selection module configured to select a potential vehicle path relative to a current vehicle movement condition; a trajectory movement condition module configured to estimate a modeled movement condition of the vehicle along the potential vehicle path; a limit comparison module configured to determine whether the modeled movement condition violates vehicle limits; and a violation indicator module configured to generate an indication of impending violation.

Techniques and systems are described for generating and using a sound localization model. A described technique includes obtaining for a building a sound sensor map indicating locations of first and second sound sensor devices in respective first and second rooms of the building; causing an autonomous device to navigate to the first room and to emit, during a time window, sound patterns at one or more frequencies within the first room; receiving sound data including first and second sound data respectively from the first and second sound sensor devices that are observed during the time window; and generating and storing a sound localization model based on the sound sensor map, autonomous device location information, and the received sound data, the model being configured to compensate for how sounds travels among rooms in at least a portion of the building such that an origin room of a sound source is identifiable.

In some embodiments, methods and systems are provided that provide for facilitating delivery, via autonomous ground vehicles, of products ordered by customers of a retailer to customer-specified restricted areas accessible by an entryway openable via an access code.

Described herein are technologies relating to computing a likelihood of an operation-influencing event with respect to an autonomous vehicle at a geographic location. The likelihood of the operation-influencing event is computed based upon a prediction of a value that indicates whether, through a causal process, the operation-influencing event is expected to occur. The causal process is identified by means of a model, which relates spatiotemporal factors and the operation-influencing events.