Virtual testing of autonomous environment control system

    公开(公告)号:US11656978B1

    公开(公告)日:2023-05-23

    申请号:US17003674

    申请日:2020-08-26

    CPC classification number: G06F11/3692 G06F11/3688 G16Y10/80 G16Y30/00

    Abstract: Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. To this end, a server may retrieve one or more routines associated with autonomous operation. The server may also generate a set of test data associated with test conditions. The server may also execute an emulator that virtually simulates autonomous environment. The test data may be presented to the routines executing in the emulator to generate output data. The server may then analyze the output data to determine a quality metric.

    COMPONENT DAMAGE AND SALVAGE ASSESSMENT

    公开(公告)号:US20220237718A1

    公开(公告)日:2022-07-28

    申请号:US17718616

    申请日:2022-04-12

    Abstract: Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicle and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the condition of components for salvage following a collision or other loss-event. To this end, the information regarding a plurality of components may be received. A component of the plurality of components may be identified for assessment. Assessment may including causing test signals to be sent to the identified component. In response to the test signal, one or more responses may be received. The received response may be compared to an expected response to determine whether the identified component is salvageable.

    Accident fault determination for autonomous vehicles

    公开(公告)号:US11386501B1

    公开(公告)日:2022-07-12

    申请号:US16803171

    申请日:2020-02-27

    Abstract: Methods and systems for determining fault for an accident involving a vehicle having one or more autonomous and/or semi-autonomous operation features are provided. According to certain aspects, performance data indicative of the performance of the features may be used to determine fault for a vehicle accident, such as a collision, by allocating fault for the accident between a vehicle operator, the autonomous operation features, or a third party. The allocation of fault may be used to determine an adjustment to an insurance policy and/or adjust coverage levels for an insurance policy. The allocation of fault may further be used to adjust risk levels or profiles associated with the autonomous or semi-autonomous operation features, which may be applied to other vehicles having the same or similar features.

    VIRTUAL TESTING OF AUTONOMOUS VEHICLE CONTROL SYSTEM

    公开(公告)号:US20210294877A1

    公开(公告)日:2021-09-23

    申请号:US15409445

    申请日:2017-01-18

    Abstract: Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation to determine the robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. A server may retrieve one or more routines associated with autonomous operation. The server may also generate a set of test data associated with test conditions. The server may also execute an emulator that virtually simulates autonomous environment. The test data may be presented to the routines executing in the emulator to generate output data. The server may then analyze the output data to determine a quality metric.

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