Abstract: Examples are disclosed for systems and methods for user interfaces of a vehicular environment, especially for autonomous vehicles wherein an orientation or attention of the vehicle occupants is not constrained to a direction of motion. In one embodiment, a system for providing visualizations within a vehicular environment comprises at least one touch-sensitive display device positioned adjacent to at least one seat within the vehicular environment and configured to display the visualizations to an occupant of the at least one seat, the at least one touch-sensitive display device moveable from a first position in front of the seat to a second position at an interior wall of the vehicular environment.

Abstract: Examples are disclosed for systems and methods for user interfaces of a vehicular environment, especially for autonomous vehicles wherein an orientation or attention of the vehicle occupants is not constrained to a direction of motion. In one embodiment, a system for providing visualizations within a vehicular environment comprises at least one touch-sensitive display device positioned adjacent to at least one seat within the vehicular environment and configured to display the visualizations to an occupant of the at least one seat, the at least one touch-sensitive display device moveable from a first position in front of the seat to a second position at an interior wall of the vehicular environment.

Abstract: A computer-implemented method and apparatus for accurately determining a vehicle's position and predicting navigation key points in real time. The method including instructing a vehicle mounted camera to capture a plurality of images, computing the angular changes between a first image and a subsequent second image, determining the vehicle's position and heading vector from the computed angular changes, collecting at least one image of the plurality of images as a first training subset, obtaining image-related coordinates of navigation key points as a second training subset related to the at least one image of the first training data subset, supplying the first and second training data subset to an artificial neural network as a training dataset, and training the artificial neural network on the training dataset to predict image-related coordinates of navigation key points indicative of road sign locations and/or turn points.

Abstract: Examples are disclosed for in-vehicle systems and methods of allocating local and remote hardware computing resources. An example system for controlling a vehicle includes a first computing device physically positioned in the vehicle, a second computing device positioned away from the vehicle, and an elastic computing module communicatively coupled to the first computing device and the second computing device, the elastic computing module configured to: determine computing and memory capacities of the first computing device and the second computing device; determine software demands of a software application for controlling a component of the vehicle; and dynamically allocate processing of the software application to the first computing device and/or the second computing device based on the computing and memory capacities of the first and second computing devices and the software demands of the software application.

Abstract: Embodiments are disclosed for an example in-vehicle computing system for a vehicle. In some embodiments, a personalized interactive experience within the vehicle is provided responsive to identification of a user in the vehicle. The user may be identified based on biometric data detection, which may include eye tracking, pupil monitoring, and head tracking in some examples. Features of the in-vehicle computing system may be selectively provided based on the identified user and/or learned data relating to the user and/or conditions of the vehicle.

Abstract: Examples are disclosed for systems and methods for user interfaces of a vehicular environment, especially for autonomous vehicles wherein an orientation or attention of the vehicle occupants is not constrained to a direction of motion. In one embodiment, a system for providing visualizations within a vehicular environment comprises at least one touch-sensitive display device positioned adjacent to at least one seat within the vehicular environment and configured to display the visualizations to an occupant of the at least one seat, the at least one touch-sensitive display device moveable from a first position in front of the seat to a second position at an interior wall of the vehicular environment.

Abstract: Embodiments are disclosed for an example in-vehicle computing system for a vehicle. In some embodiments, a personalized interactive experience within the vehicle is provided responsive to identification of a user in the vehicle. The user may be identified based on biometric data detection, which may include eye tracking, pupil monitoring, and head tracking in some examples. Features of the in-vehicle computing system may be selectively provided based on the identified user and/or learned data relating to the user and/or conditions of the vehicle.

Abstract: An embodiment sets forth a technique for interfacing with multiple intelligent personal assistants. The technique includes receiving user input comprising a trigger phrase and a command. The technique also includes identifying, via a processor and from a plurality of personal assistant services, a personal assistant service that corresponds to the trigger phrase. The processor is configured to communicate with each personal assistant service included in the plurality of personal assistant services. The technique further includes transmitting a request associated with the command to the personal assistant service, receiving a response to the request from the personal assistant service, and performing one or more operations based on the response.