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Introspective Competence Modeling for AV Decision Making

机译:AV决策的内省能力建模

摘要

A first method includes detecting, based on sensor data, an environment state; selecting an action based on the environment state; determining an autonomy level associated with the environment state and the action; and performing the action according to the autonomy level. The autonomy level can be selected based at least on an autonomy model and a feedback model. A second method includes calculating, by solving an extended Stochastic Shortest Path (SSP) problem, a policy for solving a task. The policy can map environment states and autonomy levels to actions and autonomy levels. Calculating the policy can include generating plans that operate across multiple levels of autonomy.
机译:第一种方法包括基于传感器数据的检测环境状态;根据环境状态选择动作;确定与环境状态相关的自主水平和动作;并根据自主水平执行行动。可以至少基于自主模型和反馈模型来选择自主水平。第二种方法包括通过求解扩展随机最短路径(SSP)问题来计算用于解决任务的策略。该政策可以将环境状态和自主水平映射到行动和自主程度。计算策略可以包括生成运行多个级别自主性的计划。

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