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Task Analysis of Autonomous On-road Driving

机译：自动驾驶的任务分析

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The Real-time Control System (RCS) Methodology has evolved over a number of years as a technique to capture task knowledge and organize it into a framework conducive to implementation in computer control systems. The fundamental premise of this methodology is that the present state of the task activities sets the context that identifies the requirements for all of the support processing. In particular, the task context at any time determines what is to be sensed in the world, what world model states are to be evaluated, which situations are to be analyzed, what plans should be invoked, and which behavior generation knowledge is to be accessed. This methodology concentrates on the task behaviors explored through scenario examples to define a task decomposition tree that clearly represents the branching of tasks into layers of simpler and simpler subtask activities. There is a named branching condition/situation identified for every fork of this task tree. These become the input conditions of the if-then rules of the knowledge set that define how the task is to respond to input state changes. Detailed analysis of each branching condition/situation is used to identify antecedent world states and these, in turn, are further analyzed to identify all of the entities, objects, and attributes that have to be sensed to determine if any of these world states exist. This paper explores the use of this 4D/RCS methodology in some detail for the particular task of autonomous on-road driving, which work was funded under the Defense Advanced Research Project Agency (DARPA) Mobile Autonomous Robot Software (MARS) effort (Doug Gage, Program Manager).
机译：实时控制系统（RCS）方法论作为一种捕获任务知识并将其组织成有利于在计算机控制系统中实现的框架的技术，已经发展了许多年。此方法的基本前提是任务活动的当前状态设置了上下文，该上下文标识了所有支持处理的需求。特别是，任务上下文随时确定在世界上要感知的内容，要评估的世界模型状态，要分析的情况，应调用的计划以及要访问的行为生成知识。 。该方法论着重于通过场景示例探索的任务行为，以定义任务分解树，该树清楚地表示了将任务分支为越来越简单的子任务活动的层。为该任务树的每个分支标识了一个命名分支条件/情况。这些成为知识集的if-then规则的输入条件，该条件定义任务如何响应输入状态更改。使用每个分支条件/位置的详细分析来确定先前的世界状态，然后进一步分析这些状态，以识别必须感测以确定是否存在任何这些世界状态的所有实体，对象和属性。本文详细探讨了这种4D / RCS方法在自动驾驶中的特殊任务的使用，这项工作由国防高级研究计划局（DARPA）移动自主机器人软件（MARS）资助（Doug Gage） ，程序经理）。

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