UNIFIED BOUNDARY MACHINE LEARNING MODEL FOR AUTONOMOUS VEHICLES

    公开(公告)号:US20250074451A1

    公开(公告)日:2025-03-06

    申请号:US18242328

    申请日:2023-09-05

    Abstract: A unified boundary machine learning model is capable of processing perception data received from various types of perception sensors on an autonomous vehicle to generate perceived boundaries of various semantic boundary types. Such perceived boundaries may then be used, for example, to control the autonomous vehicle, e.g., by generating a trajectory therefor. In some instances, the various semantic boundary types detectable by a unified boundary machine learning model may include at least a virtual construction semantic boundary type associated with a virtual boundary formed by multiple spaced apart construction elements, as well as an additional semantic boundary type associated with one or more other types of boundaries such as boundaries defined by physical barriers, painted or taped lines, road edges, etc.

    Remote live map system for autonomous vehicles

    公开(公告)号:US12151706B2

    公开(公告)日:2024-11-26

    申请号:US18581173

    申请日:2024-02-19

    Abstract: A live map system may be used to propagate observations collected by autonomous vehicles operating in an environment to other autonomous vehicles and thereby supplement a digital map used in the control of the autonomous vehicles. In addition, a live map system in some instances may be used to propagate location-based teleassist triggers to autonomous vehicles operating within an environment. A location-based teleassist trigger may be generated, for example, in association with a teleassist session conducted between an autonomous vehicle and a remote teleassist system proximate a particular location, and may be used to automatically trigger a teleassist session for another autonomous vehicle proximate that location and/or to propagate a suggested action to that other autonomous vehicle.

    UNIFIED BOUNDARY MACHINE LEARNING MODEL FOR AUTONOMOUS VEHICLES

    公开(公告)号:US20250077942A1

    公开(公告)日:2025-03-06

    申请号:US18241883

    申请日:2023-09-03

    Abstract: A unified boundary machine learning model is capable of processing perception data received from various types of perception sensors on an autonomous vehicle to generate perceived boundaries of various semantic boundary types. Such perceived boundaries may then be used, for example, to control the autonomous vehicle, e.g., by generating a trajectory therefor. In some instances, the various semantic boundary types detectable by a unified boundary machine learning model may include at least a virtual construction semantic boundary type associated with a virtual boundary formed by multiple spaced apart construction elements, as well as an additional semantic boundary type associated with one or more other types of boundaries such as boundaries defined by physical barriers, painted or taped lines, road edges, etc.

    REMOTE LIVE MAP SYSTEM FOR AUTONOMOUS VEHICLES

    公开(公告)号:US20250065912A1

    公开(公告)日:2025-02-27

    申请号:US18941767

    申请日:2024-11-08

    Abstract: A live map system may be used to propagate observations collected by autonomous vehicles operating in an environment to other autonomous vehicles and thereby supplement a digital map used in the control of the autonomous vehicles. In addition, a live map system in some instances may be used to propagate location-based teleassist triggers to autonomous vehicles operating within an environment. A location-based teleassist trigger may be generated, for example, in association with a teleassist session conducted between an autonomous vehicle and a remote teleassist system proximate a particular location, and may be used to automatically trigger a teleassist session for another autonomous vehicle proximate that location and/or to propagate a suggested action to that other autonomous vehicle.

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