本研究整合願景觀念、連結分析規劃法、情境規劃法、馬可夫鏈與型態分析法五種方法，建構出「馬可夫轉換情境規劃法」作為情境分析與規劃的前瞻方法，並將因素的時間轉換區分為：不變、變易、消失與不確定四類狀態。 經過研究分析，未來智慧型無人載具聚焦之關鍵決策構面為：「載具構型」、「操控方式」、「自主系統」與「產業環境」，以馬可夫鏈之時間狀態轉移觀點，呈現智慧型無人載具關鍵決策因素之未來轉變。利用馬可夫鏈不變狀態之關鍵決策因素描繪出情境發展之背景，使用型態分析法利用變易狀態、不確定狀態之關鍵決策因素建構出載具基礎情境、成功情境與技術轉換情境，並結合成整體情境，進而得知未來智慧型無人載具必須提升環境感知與自主移動能力之關鍵技術，朝工業與服務專業用途發展。 The Vision, Linkage Analysis Planning, Scenario Planning, Markov Chain and Morphological Analysis are integrated in this research project. “Markov Transition Scenario Planning” the method of Foresight Analysis is constructed and is used to distinguish types of the timable transition to the following factors: changeless, changeable (trend), disappeared, and uncertain states. After investigating these analyses, the key decision dimensions of future intelligent unmanned vehicle are “the appearance of styles”, “the vehicle configuration”, “the operating system”, “Autonomous systems” and “Industrial environment”. By using the concepts of the timable states of transition from Markov Chain, and found the changeless states of the key decision factors could be described as the background of scenario development. Moreover, by using morphological analysis with the changeable and uncertain states of the key decision factors has constructed basic scenario, success scenario and technology transfer scenario which will combine to global scenario. In the future, intelligent unmanned vehicle have to promote and increase the environment sensation and the autonomous mobile ability, in order to move toward the development of industrial and service purpose.
