Abstract: A domain specific language for use in constructing simulations within real environments is described. In an example, a computing device associated with a vehicle can receive, from one or more sensors associated with the vehicle, sensor data associated with an environment within which the vehicle is positioned. In an example, the vehicle can be an autonomous vehicle. The computing device associated with the vehicle can receive simulated data associated with one or more primitives that are to be instantiated as a scenario in the environment. The computing device can merge the sensor data and the simulated data to generate aggregated data and determine a trajectory along which the vehicle is to drive based at least in part on the aggregated data. The computing device can determine instructions for executing the trajectory and can assess the performance of the vehicle based on how the vehicle responds to the scenario.

Abstract: Techniques associated with detecting non-deterministic behavior with a component and/or subcomponents of an autonomous vehicle are discussed herein. In some cases, a simulation system may be configured to simulate operations of the autonomous vehicle and to detect changes in behavior between instances and with respect to log data or expected results. The simulation system may flag or otherwise identify components and/or subcomponents responsive to detecting potentially non-deterministic behavior.

Abstract: Techniques for determining a trajectory for an autonomous vehicle are described herein. In general, determining a route can include utilizing a search algorithm such as Monte Carlo Tree Search (MCTS) to search for possible trajectories, while using temporal logic formulas, such as Linear Temporal Logic (LTL), to validate or reject the possible trajectories. Trajectories can be selected based on various costs and constraints optimized for performance. Determining a trajectory can include determining a current state of the autonomous vehicle, which can include determining static and dynamic symbols in an environment. A context of an environment can be populated with the symbols, features, predicates, and LTL formula. Rabin automata can be based on the LTL formula, and the automata can be used to evaluate various candidate trajectories. Nodes of the MCTS can be generated and actions can be explored based on machine learning implemented as, for example, a deep neural network.

Abstract: Systems and methods to provide accurate and timely maps to autonomous vehicles. The system can utilize local map data from a plurality of electronic devices via a data gathering application (“app”). The system can compare local map data to existing global maps to identify differences and update the global maps and/or indicate that the global maps need to be updated. The system can receive camera, GPS, cellular location services, accelerometer, magnetometer, and other sensor data from the plurality of electronic devices. The system can provide incentives to users to drive on routes or proximate areas-of-interest. This can include routes or areas-of-interest that are frequently used by the autonomous vehicles in the system. This can also include routes that include accidents, construction sites, and other differences that can receive more frequent updates. The app can include a user interface (UI) to enable users to provide updates related to certain conditions.

Abstract: Systems and methods to provide visual references to passengers in vehicles to prevent motion sickness. The system can include a controller and one or more projectors and/or displays. The controller can detect movement of a vehicle and project images within the vehicle that comport with the detected movement. The system can include a projector to project images on the interior of the vehicle. The system can include one or more displays to display images inside the vehicle. The controller can receive data from one or more cameras, accelerometers, navigation units, magnetometers, and other components to detect the motion of the vehicle. The system can display visual references on the dashboard, door panels, and other interior surfaces to complete the view of passengers, or provide other visual reference, to prevent motion sickness.

Abstract: An over actuated system capable of controlling wheel parameters, such as speed (e.g., by torque and braking), steering angles, caster angles, camber angles, and toe angles, of wheels in an associated vehicle. The system may determine the associated vehicle is in a rollover state and adjust wheel parameters to prevent vehicle rollover. Additionally, the system may determine a driving state and dynamically adjust wheel parameters to optimize driving, including, for example, cornering and parking. Such a system may also dynamically detect wheel misalignment and provide alignment and/or corrective driving solutions. Further, by utilizing degenerate solutions for driving, the system may also estimate tire-surface parameterization data for various road surfaces and make such estimates available for other vehicles via a network.

Abstract: An over actuated system capable of controlling wheel parameters, such as speed (e.g., by torque and braking), steering angles, caster angles, camber angles, and toe angles, of wheels in an associated vehicle. The system may determine the associated vehicle is in a rollover state and adjust wheel parameters to prevent vehicle rollover. Additionally, the system may determine a driving state and dynamically adjust wheel parameters to optimize driving, including, for example, cornering and parking. Such a system may also dynamically detect wheel misalignment and provide alignment and/or corrective driving solutions. Further, by utilizing degenerate solutions for driving, the system may also estimate tire-surface parameterization data for various road surfaces and make such estimates available for other vehicles via a network.

Abstract: A domain specific language for use in constructing simulations within real environments is described. In an example, a computing device associated with a vehicle can receive, from one or more sensors associated with the vehicle, sensor data associated with an environment within which the vehicle is positioned. In an example, the vehicle can be an autonomous vehicle. The computing device associated with the vehicle can receive simulated data associated with one or more primitives that are to be instantiated as a scenario in the environment. The computing device can merge the sensor data and the simulated data to generate aggregated data and determine a trajectory along which the vehicle is to drive based at least in part on the aggregated data. The computing device can determine instructions for executing the trajectory and can assess the performance of the vehicle based on how the vehicle responds to the scenario.

Abstract: Techniques for determining a trajectory for an autonomous vehicle are described herein. In general, determining a route can include utilizing a search algorithm such as Monte Carlo Tree Search (MCTS) to search for possible trajectories, while using temporal logic formulas, such as Linear Temporal Logic (LTL), to validate or reject the possible trajectories. Trajectories can be selected based on various costs and constraints optimized for performance. Determining a trajectory can include determining a current state of the autonomous vehicle, which can include determining static and dynamic symbols in an environment. A context of an environment can be populated with the symbols, features, predicates, and LTL formula. Rabin automata can be based on the LTL formula, and the automata can be used to evaluate various candidate trajectories. Nodes of the MCTS can be generated and actions can be explored based on machine learning implemented as, for example, a deep neural network.

Abstract: A domain specific language for use in constructing simulations within real environments is described. In an example, a computing device associated with a vehicle can receive, from one or more sensors associated with the vehicle, sensor data associated with an environment within which the vehicle is positioned. In an example, the vehicle can be an autonomous vehicle. The computing device associated with the vehicle can receive simulated data associated with one or more primitives that are to be instantiated as a scenario in the environment. The computing device can merge the sensor data and the simulated data to generate aggregated data and determine a trajectory along which the vehicle is to drive based at least in part on the aggregated data. The computing device can determine instructions for executing the trajectory and can assess the performance of the vehicle based on how the vehicle responds to the scenario.

Abstract: Systems and processes for controlling a autonomous vehicle when the autonomous vehicle detects a disaster may include receiving a sensor signal from a sensor of a autonomous vehicle and determining that the sensor signal corresponds to a disaster definition accessible to the autonomous vehicle. The systems and processes may further include receiving a corroboration of the detected disaster and altering a drive mode of the autonomous vehicle or receiving an indication that the detected disaster was a false positive and returning to a nominal drive mode of the autonomous vehicle.

Abstract: A friction estimation system for estimating friction-related data associated with a surface on which a vehicle travels, may include a camera array including a plurality of imagers configured to capture image data associated with a surface on which a vehicle travels. The image data may include light data associated with the surface. The friction estimation system may also include an image interpreter in communication with the camera array and configured to receive the image data from the camera array and determine friction-related data associated with the surface based, at least in part, on the image data. The image interpreter may be configured to be in communication with a vehicle control system and provide the friction-related data to the vehicle control system.

Abstract: Systems and methods to provide accurate and timely maps to autonomous vehicles. The system can utilize local map data from a plurality of electronic devices via a data gathering application (“app”). The system can compare local map data to existing global maps to identify differences and update the global maps and/or indicate that the global maps need to be updated. The system can receive camera, GPS, cellular location services, accelerometer, magnetometer, and other sensor data from the plurality of electronic devices. The system can provide incentives to users to drive on routes or proximate areas-of-interest. This can include routes or areas-of-interest that are frequently used by the autonomous vehicles in the system. This can also include routes that include accidents, construction sites, and other differences that can receive more frequent updates. The app can include a user interface (UI) to enable users to provide updates related to certain conditions.

Abstract: Techniques for determining a trajectory for an autonomous vehicle are described herein. In general, determining a route can include utilizing a search algorithm such as Monte Carlo Tree Search (MCTS) to search for possible trajectories, while using temporal logic formulas, such as Linear Temporal Logic (LTL), to validate or reject the possible trajectories. Trajectories can be selected based on various costs and constraints optimized for performance. Determining a trajectory can include determining a current state of the autonomous vehicle, which can include determining static and dynamic symbols in an environment. A context of an environment can be populated with the symbols, features, predicates, and LTL formula. Rabin automata can be based on the LTL formula, and the automata can be used to evaluate various candidate trajectories. Nodes of the MCTS can be generated and actions can be explored based on machine learning implemented as, for example, a deep neural network.

Abstract: Systems and methods to provide visual references to passengers in vehicles to prevent motion sickness. The system can include a controller and one or more projectors and/or displays. The controller can detect movement of a vehicle and project images within the vehicle that comport with the detected movement. The system can include a projector to project images on the interior of the vehicle. The system can include one or more displays to display images inside the vehicle. The controller can receive data from one or more cameras, accelerometers, navigation units, magnetometers, and other components to detect the motion of the vehicle. The system can display visual references on the dashboard, door panels, and other interior surfaces to complete the view of passengers, or provide other visual reference, to prevent motion sickness.

Abstract: A coordinated component interface control framework may deterministically reproduce behavior of a data processing pipeline. The framework may include a controller that controls input to, output from, and/or execution of a component of the pipeline. The framework may also tune performance of the pipeline and/or enable parallel processing of the pipeline, even across different machines, while preserving the ability to deterministically reproduce behavior of the pipeline.

Abstract: A coordinated component interface control framework may deterministically reproduce behavior of a data processing pipeline. The framework may include a controller that controls input to, output from, and/or execution of a component of the pipeline. The framework may also tune performance of the pipeline and/or enable parallel processing of the pipeline, even across different machines, while preserving the ability to deterministically reproduce behavior of the pipeline.

Abstract: A controller may control input to, output from, and execution of a component of a data-processing pipeline via an interface. The interface facilitates replacing the component with a different and/or updated component and/or changing a type of controller that controls the component via the interface. For example, the different types of controllers may facilitate communication between components controlled by other controllers (and/or that aren't controlled by a controller), controllers that generate reproducibility data so that component behavior may be reproduced, controllers that reproduce component behavior, and/or controllers that tune performance of the data-processing pipeline, e.g., by varying input, output, and execution of respective component(s).

Abstract: Systems and methods to provide visual references to passengers in vehicles to prevent motion sickness. The system can include a controller and one or more projectors and/or displays. The controller can detect movement of a vehicle and project images within the vehicle that comport with the detected movement. The system can include a projector to project images on the interior of the vehicle. The system can include one or more displays to display images inside the vehicle. The controller can receive data from one or more cameras, accelerometers, navigation units, magnetometers, and other components to detect the motion of the vehicle. The system can display visual references on the dashboard, door panels, and other interior surfaces to complete the view of passengers, or provide other visual reference, to prevent motion sickness.

Abstract: Systems and methods to provide accurate and timely maps to autonomous vehicles. The system can utilize local map data from a plurality of electronic devices via a data gathering application (“app”). The system can compare local map data to existing global maps to identify differences and update the global maps and/or indicate that the global maps need to be updated. The system can receive camera, GPS, cellular location services, accelerometer, magnetometer, and other sensor data from the plurality of electronic devices. The system can provide incentives to users to drive on routes or proximate areas-of-interest. This can include routes or areas-of-interest that are frequently used by the autonomous vehicles in the system. This can also include routes that include accidents, construction sites, and other differences that can receive more frequent updates. The app can include a user interface (UI) to enable users to provide updates related to certain conditions.