Abstract: Various embodiments relate generally to autonomous vehicles and associated mechanical, electrical and electronic hardware, computer software and systems, and wired and wireless network communications to provide an autonomous vehicle fleet as a service. In particular, a method may include receiving, at an autonomous vehicle system, a command to control an ambient feature associated with the autonomous vehicle system. One or more courses of action may be determined based on the command. In addition, one or more probabilistic models associated with the one or more courses of action may also be determined. Based on the one or more probabilistic models, confidence levels may also be determined to form a subset of the one or more courses of action. A course of action from the subset of the one or more courses of action may then be executed at the autonomous vehicle system responsive to the command.

Abstract: Systems, apparatus and methods to multiple levels of redundancy in torque steering control and propulsion control of an autonomous vehicle include determining that a powertrain unit of the autonomous vehicle is non-operational and disabling propulsion operation of the non-operational powertrain unit and implementing torque steering operation in another powertrain unit while propelling the autonomous vehicle using other powertrain units that are configured to implement torque steering operation and propulsion operation.

Abstract: Various embodiments relate generally to autonomous vehicles and associated mechanical, electrical and electronic hardware, computer software and systems, and wired and wireless network communications to provide an autonomous vehicle fleet as a service. In particular, a method may include receiving an indication of a sensor anomaly, determining one or more sensor recovery strategies based on the sensor anomaly, and executing a course of action that ensures the autonomous vehicle system operates within accepted parameters. Alternative sensors may be relied upon to cover for the sensor anomaly, which may include a failed sensor while the autonomous vehicle is in operation.

Abstract: Systems and methods implemented in algorithms, software, firmware, logic, or circuitry may be configured to process data and sensory input to determine whether an object external to an autonomous vehicle (e.g., another vehicle, a pedestrian, road debris, a bicyclist, etc.) may be a potential collision threat to the autonomous vehicle. The autonomous vehicle may be configured to implement active safety measures to avoid the potential collision and/or mitigate the impact of an actual collision to passengers in the autonomous vehicle and/or to the autonomous vehicle itself. Interior safety systems, exterior safety systems, a drive system or some combination of those systems may be activated to implement active safety measures in the autonomous vehicle.

Abstract: Systems and methods implemented in algorithms, software, firmware, logic, or circuitry may be configured to process data and sensory input to determine whether an object external to an autonomous vehicle (e.g., another vehicle, a pedestrian, road debris, a bicyclist, etc.) may be a potential collision threat to the autonomous vehicle. The autonomous vehicle may be configured to implement active safety measures to avoid the potential collision and/or mitigate the impact of an actual collision to passengers in the autonomous vehicle and/or to the autonomous vehicle itself. Interior safety systems, exterior safety systems, a drive system or some combination of those systems may be activated to implement active safety measures in the autonomous vehicle.

Abstract: Various embodiments relate generally to autonomous vehicles and associated mechanical, electrical and electronic hardware, computer software and systems, and wired and wireless network communications to provide an autonomous vehicle fleet as a service. In particular, a method may include monitoring a fleet of vehicles, at least one of which is configured to autonomously transit from a first geographic region to a second geographic region, detecting data indicating an event associated with the vehicle having a calculated confidence level, receiving data representing a subset of candidate trajectories responsive to detecting the event, which is associated with a planned path for the vehicle, identifying guidance data to select from one or more of the candidate trajectories as a guided trajectory, receiving data representing a selection of a candidate trajectory, and transmitting the selection of the candidate trajectory as of the guided trajectory to the vehicle.

Abstract: Systems, apparatus and methods implemented in algorithms, hardware, software, firmware, logic, or circuitry may be configured to process data and sensory input to determine whether an object external to an autonomous vehicle (e.g., another vehicle, a pedestrian, road debris, a bicyclist, etc.) may be a potential collision threat to the autonomous vehicle. The autonomous vehicle may be configured to implement interior active safety systems to protect passengers of the autonomous vehicle during a collision with an object or during evasive maneuvers by the autonomous vehicle, for example. The interior active safety systems may be configured to provide passengers with notice of an impending collision and/or emergency maneuvers by the vehicle by tensioning seat belts prior to executing an evasive maneuver and/or prior to a predicted point of collision.

Abstract: Various embodiments relate generally to autonomous vehicles and associated mechanical, electrical and electronic hardware, computer software and systems, and wired and wireless network communications to provide an autonomous vehicle fleet as a service. More specifically, systems, devices, and methods are configured to initiate modification of trajectories to influence navigation of autonomous vehicles. In particular, a method may include receiving a teleoperation message via a communication link from an autonomous vehicle, detecting data from the teleoperation message specifying an event associated with the autonomous vehicle, identifying one or more courses of action to perform responsive to detecting the data specifying the event, and generating visualization data to present information associated with the event to a display of a teleoperator computing device.

Abstract: Systems, apparatus and methods to implement sectional design (e.g., in quadrants) of an autonomous vehicle may include modular construction techniques to assemble an autonomous vehicle from multiple structural sections. The multiple structural sections may be configured to implement radial and bilateral symmetry. A structural section based configuration may include a power supply configuration (e.g., using rechargeable batteries) including a double-backed power supply system. The power supply system may include a kill switch disposed on a power supply (e.g., at an end of a rechargeable battery). The kill switch may be configured to disable the power supply system in the event of an emergency or after a collision, for example. The radial and bilateral symmetry may provide for bi-directional driving operations of the autonomous vehicle as the vehicle may not have a designated front end or a back end.