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Title: 以基於混合多準則決策模式之情境分析與專利探勘定義無人電動車平台
Defining an Autonomous Vehicle Platform by Using Hybrid MCDM Methods Based Scenario Writing and Patent Mining Techniques
Authors: 黃啟祐
Huang, Chi-Yo
Chang, Wan-Jung
Keywords: 專利探勘
Patent Mining
Association Rule Mining
Autonomous Vehicle
Scenario Analysis
Platform Development
Automatic driving
Issue Date: 2018
Abstract: 隨著科技的快速進展,汽車產業將在未來的15年經歷一場大革命,未來全球對於智慧駕駛、自動駕駛與電動車的重視,將會讓車用電子產業站穩更重要的地位。從2009年Google開始測試無人駕駛車後,越來越多科技巨擘及汽車製造商加入這場革命並相爭佈局專利,從光達技術、奈米天線感測技術、人工智慧到已成熟的先進駕駛輔助系統、資通訊娛樂系統等相關技術皆爭相投入大筆資金進行研發。基於未來無人駕駛車將成為市場的主流趨勢,然而目前研究並未揭示針對不同情境下的無人駕駛車平台架構,因此,本研究利用專利探勘技術,針對近幾年所增加無人駕駛車的相關專利文獻進行文字探勘,找出專利的重要關鍵字或隱含的技術關鍵字,並透過關聯規則探勘方法模擬出無人電動車的平台。而後,基於混合多準則決策模式及情境分析法建立不同的情境,並針對所選出的情境,進而分析該情境中的無人電動車的可能著重的技術及平台架構為何。對於後進者發展能大幅降低研發成本及失敗風險,更準確抓住未來技術發展趨勢。
With the rapid advancementof technology, the world will most certainly experience a revolution in the automotive industry within the next 15 years. This revolution is being driven by the concurrence of electrical vehicles, self-driving cars and driving intelligence, which if the pattern holds true, it would open the door to new leading-edge innovations that would put the automotive industry in a superior position in the future. Since 2009, Google began testing unmanned vehicles with one goal in mind; to build an autonomous vehicle by 2020. With this, other technology giants and car manufactures joined to compete in the growing industry by pouring large sums of money into research and development and obtaining patents including LiDAR technology, Nano-antenna sensing technology, artificial intelligence, Infotainment systems and Advanced Driver Assistance Systems (ADAS). Based on the future of autonomous vehicles there may be a market trend. However, current study does not reveal the existing standard platform architecture in different scenarios for autonomous vehicles. This study use Patent Mining to conduct research by obtaining relevant patent documents of autonomous vehicles in recent years to analyze key findings and information within mainstream technology. Moreover, through the Association Rule Mining method to simulate the platform of the autonomous vehicle. This study will also use Hybrid MCDM and Scenario Analysis to establish various scenarios then analyze and explore the platforms of autonomous vehicles. For late entrants, it may significantly reduce the cost of R& D, risk and enhance accuracy of future technology trends.
Other Identifiers: G060570048H
Appears in Collections:學位論文

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