Abstract: Systems and methods are provided for determining driver surprise. The system can receive image data of a driver's pupils and video data of the driver's face over a time interval and determine a diameter of the driver's pupils over the time interval based on the image data. This diameter can be used to generate a pupil confidence value based on the diameter over the time interval. The system can extract facial features from the video data and generate a facial confidence value based on the facial features. A first weight can be applied to the pupil confidence value and a second weight can be applied to the facial confidence value to determine whether the driver is expressing surprise.

Abstract: A method for controlling an ego vehicle in an environment includes associating, by a velocity model, one or more objects within the environment with a respective velocity instance label. The method also includes selectively, by a recurrent network of the taillight recognition system, focusing on a selected region of the sequence of images according to a spatial attention model for a vehicle taillight recognition task. The method further includes concatenating the selected region with the respective velocity instance label of each object of the one or more objects within the environment to generate a concatenated region label. The method still further planning a trajectory of the ego vehicle based on inferring, at a classifier of the taillight recognition system, an intent of each object of the one or more objects according to a respective taillight state of each object, as determined based on the concatenated region label.

Abstract: System, methods, and other embodiments described herein relate to steering a vehicle based during loss of traction. In one arrangement, a method for steering a vehicle during loss of traction is disclosed. The method includes, responsive to detecting a slipping tire of a vehicle losing traction with a road, automatically steering the vehicle separately from an input of a steering wheel of the vehicle to cause the vehicle to follow a path. The method also includes decoupling control of a pair of front tires of the vehicle by the steering wheel. The method further includes rotating, independently of an input to the steering wheel and in parallel with steering the vehicle, the steering wheel to match an actual yaw of the vehicle.

Abstract: A method for a shared control, dynamic driving system is described. The method includes determining a vehicle command requested by a vehicle operator of an ego vehicle. The method also includes predicting the ego vehicle entering an unstable, controllable operating range if the vehicle command is performed. The method further includes adjusting the vehicle command to maintain control of the ego vehicle in the unstable, controllable operating range. The method also includes performing an adjusted vehicle command to operate the ego vehicle in the unstable, controllable operating range while maintaining recovery stability to transition to a safe operating range.

Abstract: Systems and methods disclosed include identifying a topic and a perspective of an input text to be sent to a receiver, determining a receiver perspective based on the topic of the input text and a receiver persona associated with the receiver, determining, by comparing the perspective of the input text and the perspective of the receiver, whether the input text includes a language having an offensive probability beyond an offensive probability threshold, after determining that the input text includes the language having the offensive probability beyond the offensive probability threshold, providing an option to modify the input text on a user interface of the sender, and modifying the input text to have the offensive probability below the offensive probability threshold when the option is selected.

Abstract: Methods and systems disclosed are directed to a virtual simulation of chargers in a real-world environment having a wiring system using, a camera, an augmented reality (AR) interface, and a processor operable to generate a virtual charger representing a charger superimposed on the real-world environment, receive data responsive to a user interaction using the AR interface to operate the virtual charger, update the virtual charger superimposed on the real-world environment based on the operation, and wherein the virtual charger includes a connector and a charging cable including a first end and a second end, the first end operable to be connected to the connector, and the second end operable to be connected to the wiring system.

Abstract: Systems, methods, and other embodiments described herein relate to organizing and altering selected images from a style map with learning models through factoring style dimensions. In one embodiment, a method includes generating a style map by transforming and clustering information from an image dataset with a visualization model within a computation space having reduced dimensionality, and the style map includes style features derived from the image dataset. The method also includes comparing images selected from the style map using scores for dimensions associated with semantic attributes to form a comparison map. The method also includes mixing visual styles of the images from the comparison map with a generative model that computes representation interpolations within a latent space, the generative model outputting stylized images in an array. The method also includes communicating the array to a development system.

Abstract: System, methods, and other embodiments described herein relate to coordinating and optimizing prediction by a model using intermediate data and vehicle-to-vehicle (V2V) communications that improves bandwidth utilization. In one embodiment, a method includes processing acquired data, by a subject vehicle using a prediction model, to execute a vehicle task associated with navigating a driving scene. The method also includes extracting processed data according to the acquired data from intermediate activations of layers within the prediction model according to a cooperation model. The method also includes quantifying relevancy of the processed data, for a target vehicle, to select a subset using the cooperation model. The method also includes communicating the subset to a selected vehicle having the prediction model for additional prediction according to the relevancy and available resources to transmit the subset.

Abstract: A method for self-calibrating alignment between image data and point cloud data utilizing a machine learning model includes receiving, with an electronic control unit, image data from a vision sensor and point cloud data from a depth sensor, implementing, with the electronic control unit, a machine learning model trained to: align the point cloud data and the image data based on a current calibration, detect a difference in alignment of the point cloud data and the image data, adjust the current calibration based on the difference in alignment, and output a calibrated embedding feature map based on adjustments to the current calibration.

Abstract: Systems and methods are provided for verifying the accuracy of a map. Information regarding objects, such as roadway or roadway-related elements may be encoded into a map to be used for navigation and/or control of a vehicle, such as an autonomous vehicle. In order to verify that the map accurately reflects the roadway or roadway-related elements making up a section of roadway, the vehicle may be driven/ridden along the same section of roadway. A camera feed can be captured of this subsequent traversal of the section of roadway to check if the map includes the requisite roadway or roadway-related elements. The known roadway or roadway-related elements can be occluded from view in the camera feed. Accordingly, if any roadway or roadway-related elements do appear in the camera feed, they can be more easily detected by a verifier, and the processor verification is simplified.

Abstract: Systems and methods are provided for variable actuation and release of a vehicle's brake hold mechanism/function. A brake hold device may be implemented as a “tuner” or controller that can connect to and override, e.g., the default functionality of an existing brake hold mechanism of a vehicle. Delays in exiting a brake hold state, repetitive actuation of an accelerator to exit a brake hold state, and other shortcomings associated with the conventional operation of brake hold mechanisms may be avoided by taking into account relevant vehicle operating conditions or environmental/road/traffic conditions.

Abstract: A vehicle system includes one or more sensors configured to capture aspects of an environment and a computing device. The computing device is configured to receive information about the environment captured by the one or more sensors, determine one or more structures within the environment based on the received information, select a kernel that is parameterized for predicting a vehicle trajectory based on the one or more structures determined within the environment, and perform a convolution of the selected kernel and an array defining the environment, wherein the convolution predicts a future trajectory of a vehicle within the environment.

Abstract: Systems and methods are provided for implementing soft model assertions (SMA) system and techniques designed to monitor and improve Machine Learning (ML) model quality by to detecting errors within the one or more ML models. SMA techniques and systems are distinctly designed to leverage: 1) a user's ability to specify features over data; and 2) large, existing datasets of organizations, in a manner that can improve the accuracy and quality of predicting potential errors in Machine Learning (ML) models. A SMA system can include a controller device receiving predictions generated based on the ML models and output from the SMA system. The controller performs autonomous operations of the system in response to determining that the one or more detected errors within the one or more ML models yield a high certainty of errors in the predictions. The SMA system also includes a domain specific language and a severity score module.

Abstract: A system for producing a depth map can include a processor and a memory. The memory can store a neural network. The neural network can include an encoding portion module, a multi-frame feature matching portion module, and a decoding portion module. The encoding portion module can include instructions that, when executed by the processor, cause the processor to encode an image to produce single-frame features. The multi-frame feature matching portion module can include instructions that, when executed by the processor, cause the processor to process the single-frame features to produce information. The decoding portion module can include instructions that, when executed by the processor, cause the processor to decode the information to produce the depth map. A first training dataset, used to train the multi-frame feature matching portion module, can be different from a second training dataset used to train the encoding portion module and the decoding portion module.

Abstract: Systems and methods are provided for validating a map via automatic test generation for multiple test route subsections. Autonomous vehicles required accurate maps. As such, new maps may be added and/or maps map be updated frequently. Verifying these maps requires testing. Maps may be validated via automatic test generation by obtaining route information identifying a route in the map for an autonomous vehicle. The route may be segmented into multiple test route subsections. Features corresponding to one or more of the test route subsections may be identified. One or more validation tests corresponding to the test route subsections may be generated based on a simulated autonomous vehicle traversing the one or more road features. For example, multiple validation tests for corresponding test route subsections may be generated and executed in parallel.

Abstract: Systems and methods described herein relate to adjusting presentation of media content in a vehicular environment. In one embodiment, a system for adjusting presentation of media content in a vehicular environment estimates a time at which an operational design domain (ODD) boundary will occur for a vehicle that is operating in an at least semi-autonomous driving mode. The system also processes automatically a media-content item presented to an occupant of the vehicle to generate a modified media-content item, the modified media-content item having a duration that results in presentation of the modified media-content item concluding at a predetermined time not later than the estimated time.

Abstract: A method for managing operation of a vehicle includes detecting, while the vehicle is operating, an assistance condition that triggers activation of one or more assistance components of a set of assistance components associated with a driver assistance system, the vehicle having been retrofitted to include an autonomous driving system. The method also includes determining whether the autonomous driving system satisfies a respective safety condition associated with each of the one or more assistance components without activation of the one or more assistance components. The method further includes preventing the one or more assistance components from activating in accordance with determining the autonomous driving system satisfies the safety condition.

Abstract: Robots for lifting objects are disclosed. In one embodiment, a robot includes a rail system, a body structure coupled to the rail system, a first arm coupled to a first side of the body structure, one or more first arm actuators providing the first arm with multiple degrees of freedom, a second arm coupled to a second side of the body structure, one or more second arm actuators providing the second arm with multiple degrees of freedom, and a lift actuator operable to move the body structure along the rail system. The one or more first arm actuators and the one or more second arm actuators are operable to wrap the first arm and the second arm around an object and hold the object against the body structure. The lift actuator is operable to move the body structure such that the object is lifted on the rail system.

Abstract: Systems, methods, and other embodiments described herein relate to steering a vehicle based on an intended yaw rate during loss of traction. In one arrangement, a method for steering a vehicle during loss of traction is disclosed. The method includes detecting a slipping tire of a vehicle losing traction with a road. The method also includes decoupling control of a pair of front tires of the vehicle by a steering wheel of the vehicle. The method also includes identifying an intended yaw rate for controlling the vehicle by detecting an angle of the steering wheel while the slipping tire does not have traction. The method further includes steering the vehicle separately from an input of a steering wheel of the vehicle to cause intended yaw rate.

Abstract: System, methods, and other embodiments described herein relate to generating a response of a vehicle to a virtual rumble strip. In one embodiment, a method includes determine that a virtual boundary corresponding to a real-world location in proximity of a vehicle has been crossed as the vehicle travels based upon first sensor data generated by the vehicle. The method further includes determine information about an environment of the vehicle as the virtual boundary is crossed based upon second sensor data generated by the vehicle. The method also includes activate an actuator of a seat of the vehicle such that haptic feedback is delivered to the seat, wherein the haptic feedback is based upon the information about the environment and a type of a virtual rumble strip.