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: Systems, methods, and apparatuses described herein are directed to automated vehicle diagnostics and maintenance. For example, vehicles can include sensors monitoring vehicle components, for perceiving objects and obstacles in an environment, and for navigating the vehicle to a destination. Data from these and other sensors can be leveraged to track a performance of the vehicle over time to determine a state of vehicle components, and/or changes to acceleration/deceleration and steering behavior of the vehicle over time. As issues for servicing are determined, the methods, apparatuses, and systems can include automated scheduling of vehicle maintenance. For example, based on a determination of the potential issues based on sensor data and/or user indications, vehicle maintenance can be scheduled to be performed in the field or at a service center. Technicians can be assigned to perform vehicle maintenance based on the servicing issue and/or on capabilities of the technician.

Abstract: Systems, methods, and apparatuses described herein are directed to vehicle self-diagnostics. For example, a vehicle can include sensors monitoring vehicle components, for perceiving objects and obstacles in an environment, and for navigating the vehicle to a destination. Data from these and other sensors can be leveraged to determine a behavior associated with the vehicle. Based at least in part on determining the behavior, a vehicle can determine a fault and query one or more information sources associated with the vehicle to diagnose the fault. Based on diagnosing the fault, the vehicle can determine instructions for redressing the fault. The vehicle can diagnose the fault in near-real time, that is, while driving or otherwise in the field.

Abstract: Techniques for generating and executing trajectories to guide autonomous vehicles are described. In an example, a first computer system associated with an autonomous vehicle can generate, at a first operational frequency, a route to guide the autonomous vehicle from a current location to a target location. The first computer system can further determine, at a second operational frequency, an instruction for guiding the autonomous vehicle along the route and can generate, at a third operational frequency, a trajectory based at least partly on the instruction and real-time processed sensor data. A second computer system that is associated with the autonomous vehicle and is in communication with the first computer system can execute, at a fourth operational frequency, the trajectory to cause the autonomous vehicle to travel along the route. The separation of the first computer system and the second computer system can provide enhanced safety, redundancy, and optimization.

Abstract: Systems, methods, and apparatuses described herein are directed to automated vehicle diagnostics and maintenance. For example, vehicles can include sensors monitoring vehicle components, for perceiving objects and obstacles in an environment, and for navigating the vehicle to a destination. Data from these and other sensors can be leveraged to track a performance of the vehicle over time to determine a state of vehicle components, and/or changes to acceleration/deceleration and steering behavior of the vehicle over time. As issues for servicing are determined, the methods, apparatuses, and systems can include automated scheduling of vehicle maintenance. For example, based on a determination of the potential issues based on sensor data and/or user indications, vehicle maintenance can be scheduled to be performed in the field or at a service center. Technicians can be assigned to perform vehicle maintenance based on the servicing issue and/or on capabilities of the technician.

Abstract: Techniques for generating and executing trajectories to guide autonomous vehicles are described. In an example, a first computer system associated with an autonomous vehicle can generate, at a first operational frequency, a route to guide the autonomous vehicle from a current location to a target location. The first computer system can further determine, at a second operational frequency, an instruction for guiding the autonomous vehicle along the route and can generate, at a third operational frequency, a trajectory based at least partly on the instruction and real-time processed sensor data. A second computer system that is associated with the autonomous vehicle and is in communication with the first computer system can execute, at a fourth operational frequency, the trajectory to cause the autonomous vehicle to travel along the route. The separation of the first computer system and the second computer system can provide enhanced safety, redundancy, and optimization.