Abstract: A biometric evaluation system for a vehicle includes a vision sensor configured to detect a biometric quality of a user. The biometric evaluation system also includes an operational system for the vehicle. At least one processor is in communication with the vision sensor. The processor is configured to execute a first classification algorithm that performs a first biometric validation based on the biometric quality to estimate a state of the user. The first classification algorithm requires a first service latency. In response to an outcome of the first biometric validation, the at least one processor is further configured to execute a second classification algorithm that performs a second biometric validation to confirm the state of the user. The second classification algorithm requires a second service latency greater than the first service latency. The processor is further configured to communicate a signal to modify operation of the vehicle.

Abstract: A method to prevent intoxicated operation is described. The method includes providing instructions to a vehicle user to position a vehicle user body portion posture in a predefined alignment. The method further includes obtaining the vehicle user body portion posture from a first vehicle detector, and determining whether the vehicle user body portion posture is in the predefined alignment. The method includes activating a plurality of vehicle visual indicators to illuminate in a predefined manner when the vehicle user body portion posture is in the predefined alignment. The method further includes providing instructions to the vehicle user to move vehicle user eyes to track the plurality of vehicle visual indicators, and obtaining a vehicle user eye movement from a second vehicle detector. The method further includes determining whether the vehicle user eye movement meets a predetermined condition, and actuating a control action accordingly.

Abstract: A computer, including a processor and a memory, the memory including instructions to be executed by the processor to acquire a first image with a visible and NIR light camera and acquire a second image with an infrared camera. The instructions can include further instructions to determine whether the second image includes a live human face by comparing a first infrared profile included in the second image with second infrared profile included in a previously acquired third image acquired with the infrared camera; and when the second image includes the live human face, output the first image.

Abstract: Embodiments describe a system configured with a brain machine interface (BMI) system implemented in a vehicle for performing vehicle functions using electrical impulses from motor cortex activity in a user's brain. The system uses fuzzy states for increased robustness. The fuzzy states are defined by sets of Gaussian kernel-type membership functions that are defined for steering and velocity action function states. The membership functions define fuzzy states that provide overlapping control tiers for increasing and decreasing vehicle functionality. An autonomous vehicle may perform control and governance of transitions between membership functions that may overlap, resulting in smooth transitioning between the states.

Abstract: A vehicle for improved user authentication is provided. The vehicle includes a biometric sensor; and a controller programmed to initiate a biometric authentication of a user within a vicinity of a vehicle using data received from the biometric sensor, and responsive to occurrence of a secondary trigger condition initiated by the user to gain access to the vehicle, complete the authentication to grant or deny access to the user. A system for remote management of lockout states for a vehicle is provided. A server is programmed to receive a lockout notification from the vehicle, responsive to occurrence of a failed access attempt using an access modality, the lockout notification including contextual information with respect to the occurrence of the failed access attempt; and send, responsive to the lockout notification, an indication of an administrative action to be performed by the vehicle.

Abstract: Based on a measured intensities of first and second light sources while both the first and second light sources are actuated, and a default secondary illuminator output intensity, a computer may determine an adjusted secondary illuminator output intensity and actuate the secondary light source to output light at the adjusted secondary light source output intensity.

Abstract: A transfer key system for a vehicle may include a key receptacle configured to detect the presence of a transfer key, and a controller configured to receive key status signals from the key receptacle, and activate the transfer key as an active transfer key in response to the status signal indicating a removal of the transfer key from the key receptacle and receiving an authentication signal from a user.

Abstract: A computer, including a processor and a memory, the memory including instructions to be executed by the processor to acquire a first image by illuminating a first object with a first light beam, segment the first image of the first object to determine regions that correspond to a first surface material and determine a first measure of pixel values in regions of the first image that correspond to the first surface material. The instructions include further instructions to perform a comparison of the first measure of pixel values to a second measure of pixel values determined from a second image of a second object, wherein the second image is previously acquired by illuminating the second object with a second light beam and when the comparison determines that the first measure is equal to the second measure of pixel values within a tolerance, determine that the first object and the second object are a same object.

Abstract: A first frame of image data is captured at a first illumination intensity during a first time segment. A second frame of image data is captured at a second illumination intensity during a second time segment. The first frame and the second frame are combined and outputted as a compensated frame.

Abstract: Systems and methods include techniques for determining whether to use underbalanced coiled tubing drilling (UBCTD) or conventional drilling with hydraulic fracturing to drill a new well in deep and tight reservoirs with slow rate of penetration issues. Estimates of geomechanical properties and image log processing for past-drilled wells are completed first, then three-dimensional (3D) property modeling and natural fracture prediction (NFP) for the domain are conducted. Then a 3D geomechanics model is generated. After this the rock properties and NFP along the planned well trajectory are extracted. The diagenetic rock typing is evaluated. Required breakdown pressure for hydraulic fracturing is calculated. A determination based on the diagenetic rock typing and required breakdown pressure is made whether UBCTD or conventional drilling with hydraulic fracturing should be used for a new well.

Abstract: Upon authorizing a user via challenge biometric data, user data is determined to be updated based on detecting a trigger. Upon detecting the trigger prior to authenticating the user, the user data is updated with the challenge biometric data based on authenticating the user. Upon detecting the trigger after authenticating the user, the user data is updated with updated challenge biometric data based on a confidence score for the second biometric data exceeding a threshold. Structure components are controlled based on the updated user data.

Abstract: A facial recognition authentication system and method include obtaining a current image in response to a request for facial recognition authentication of a user. A set of current image features are generated from the input image. Live image features and spoof image features are retrieved for the user. Then a determination is output that the input image is one of live or spoofed based on a comparison of the current image features to the live image features and the spoof image features.

Abstract: A system includes an illumination source operable at an adjustable duty cycle, a camera arranged to detect illumination from the illumination source, and a computer communicatively coupled to the illumination source and the camera. The duty cycle indicates a proportion of time that the illumination source is illuminated in a repeating pattern. The computer is programmed to operate the illumination source with the duty cycle at a baseline duty cycle in response to failing to detect an object having a preset type in image data from the camera, and operate the illumination source with the duty cycle at a high duty cycle in response to detecting the object having the preset type in the image data from the camera. The high duty cycle has the illumination source illuminated for a greater proportion of time than the baseline duty cycle.

Abstract: Systems, methods, and devices for verifying an identity of a user of a vehicle. The method includes receiving user authentication data from a vehicle sensor and generating a transaction token comprising the user authentication data. The method includes transmitting the transaction token to a blockchain database. The method includes receiving a message from the blockchain database comprising one or more of: a request for additional user authentication data; or an indication that a rider authentication server has verified the identity of the user.

Abstract: Method and apparatus are disclosed for interface verification for vehicle remote park-assist. An example vehicle system includes a mobile device and a vehicle autonomy unit. The mobile device includes a touchscreen and a controller. The controller is to present, via the touchscreen, an interface of a remote parking app and receive, via the touchscreen, an input responsive to the presentation of the interface. The vehicle autonomy unit receives an input signal from the mobile device and an input classifier coupled to the vehicle autonomy unit verifies the received input signal complies with an input classification.

Abstract: A system receives a request to engage one or more vehicle micro-services on behalf of a vehicle feature. The system accesses a manifest associated with the vehicle feature, the manifest including the one or more micro-services and configurations to be associated with instances of the one or more micro-services launched on behalf of the vehicle feature. The system requests launch of each of the micro-services and the associated configurations from a vehicle process responsible for micro-service launch, to build a pipeline for the vehicle feature and translates results generated by at least one micro-service of the pipeline into a format predefined as suitable for use by the vehicle feature.

Abstract: A vehicle system receives a request for a first vehicle micro-service to be executed on behalf of a first feature and to be executed having a configuration included in the request. The system determines whether the first micro-service with the configuration is already executing on behalf of a second feature. The system determines if vehicle resources will support an instance of the first micro-service with the configuration when the first micro-service with the configuration is not already executing and, responsive to determining that vehicle resources will support the instance, launches the requested first micro-service with the configuration. The system additionally registers the instance along with the configuration and any features on behalf of which the instance is functioning.

Abstract: Embodiments describe a vehicle configured with a brain machine interface (BMI) for a vehicle computing system to control vehicle functions using electrical impulses from motor cortex activity in a user's brain. A BMI training system trains the BMI device to interpret neural data generated by a motor cortex of a user and correlate the neural data to a vehicle control command associated with a neural gesture emulation function. A BMI system onboard the vehicle may receive a neural data feed of neural data from the user using the trained BMI device, determine, a user intention for a control instruction to control a vehicle infotainment system using the neural data feed, and perform an action based on the control instruction. The vehicle may further include a headrest configured as a Human Machine Interface (HMI) device that reads the electrical impulses without invasive electrode connectivity.

Abstract: A liveliness prediction output is provided from a liveliness biometric analysis task that is determined by a deep neural network based on an image provided from an image sensor wherein the liveliness biometric analysis task is performed in a deep neural network that includes a common feature extraction neural network and a plurality of task-specific neural networks including a face detection neural network, a body pose neural network and a liveliness neural network including a region of interest (ROI) detection neural network and a texture analysis neural network to determine the liveliness biometric analysis task by inputting the image to the common feature extraction neural network to determine latent variables. The latent variables can be input to the face detection neural network and the liveliness neural network. Output from the face detection neural network can be input to the ROI detection neural network.

Abstract: A computer, including a processor and a memory, the memory including instructions to be executed by the processor to acquire a first image from a first camera by illuminating a first object with a first light and determine an object status as one of a real object or a counterfeit object by comparing a first measure of pixel values corresponding to the first object to a threshold.