Abstract: An artificial intelligence perception system for detecting one or more objects includes one or more processors, at least one sensor, and a memory device. The memory device includes an image capture module, an object identifying module, and a logical scaffold module. The image capture module and the object identifying module cause the one or more processors to obtain sensor information of a field of view from a sensor, identify an object within the sensor information, and determine at least one property of the object. The logical scaffold module causes the one or more processors to determine, by a logical scaffold, when the at least one property of the object as determined by the object identifying module is one of a true condition or a false condition.

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: An artificial intelligence perception system for detecting one or more objects includes one or more processors, at least one sensor, and a memory device. The memory device includes an image capture module, an object identifying module, and a logical scaffold module. The image capture module and the object identifying module cause the one or more processors to obtain sensor information of a field of view from a sensor, identify an object within the sensor information, and determine at least one property of the object. The logical scaffold module causes the one or more processors to determine, by a logical scaffold, when the at least one property of the object as determined by the object identifying module is one of a true condition or a false condition.

Abstract: Systems, apparatus, and methods implemented in algorithms, software, firmware, logic, or circuitry may be configured to process data and sensory input in real-time to determine whether an object external to an autonomous vehicle may be a potential collision threat to the autonomous vehicle. The autonomous vehicle may be configured to deploy one or more bladders positioned external to the autonomous vehicle to absorb forces from an impact to the vehicle by the object. A perception system of the vehicle may receive a sensor signal and generate object data associated with the object. A planner system of the vehicle may process the object data to predict an impact time and an impact location on the vehicle. The planner system may cause a drive system of the vehicle to maneuver the vehicle to position an impact-absorbing structure and/or one or more bladders of the vehicle to coincide with the predicted impact location.

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: 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: 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: 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: Systems, apparatus, and methods implemented in algorithms, software, firmware, logic, or circuitry may be configured to process data and sensory input in real-time to determine whether an object external to an autonomous vehicle may be a potential collision threat to the autonomous vehicle. The autonomous vehicle may be configured to deploy one or more bladders positioned external to the autonomous vehicle to absorb forces from an impact to the vehicle by the object. A perception system of the vehicle may receive a sensor signal and generate object data associated with the object. A planner system of the vehicle may process the object data to predict an impact time and an impact location on the vehicle. The planner system may cause a drive system of the vehicle to maneuver the vehicle to position an impact-absorbing structure and/or one or more bladders of the vehicle to coincide with the predicted impact location.

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.