Evaluating operator reliance on vehicle alerts

    公开(公告)号:US11842300B1

    公开(公告)日:2023-12-12

    申请号:US16992198

    申请日:2020-08-13

    CPC classification number: G06Q40/08

    Abstract: A system and computer-implemented method detect and act upon operator reliance to vehicle alerts. The system and method include receiving user profile data of an operator that includes a baseline of at least one driving activity aided by activation of an alert from a feature of an Advanced Driver Assistance System (ADAS). The system and method may include receiving historical ADAS alert frequency data including a history of at least one driving activity aided by activation of the alert from the ADAS feature. The system and method may compare the user profile data with the historical ADAS alert frequency data, determine a reliance level based upon the comparing, and set at least a portion of an operator profile associated with the operator with the reliance level. As a result, a risk averse driver, and/or proper responsiveness to vehicle alerts may be rewarded with insurance-cost savings, such as increased discounts.

    MANUAL CONTROL RE-ENGAGEMENT IN AN AUTONOMOUS VEHICLE

    公开(公告)号:US20230315090A1

    公开(公告)日:2023-10-05

    申请号:US18206414

    申请日:2023-06-06

    CPC classification number: G05D1/0061 G05D1/0088 B60W2050/007

    Abstract: Vehicles may have the capability to navigate according to various levels of autonomous capabilities, the vehicle having a different set of autonomous competencies at each level. In certain situations, the vehicle may shift from one level of autonomous capability to another. The shift may require more or less driving responsibility from a human operator. Sensors inside the vehicle collect human operator parameters to determine an alertness level of the human operator. An alertness level is determined based on the human operator parameters and other data including historical data or human operator-specific data. Notifications are presented to the user based on the determined alertness level that are more or less intrusive based on the alertness level of the human operator and on the urgency of an impending change to autonomous capabilities. Notifications may be tailored to specific human operators based on human operator preference and historical performance.

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