基於多準則之情境分析與專利探勘方法選擇光達之開發與改善創新策略

Abstract

隨著科技的創新發展，交通技術日益革新，無人駕駛車的技術也應運而生。無人車的相關技術發展有可能可以大大的提高安全性，有助於減少交通擁塞，提供更多行車選擇。隨著Google、Tesla等公司相繼推出無人車並多次在道路上試駕，也影響了其他業者的布局或研發策略。本研究分析無人車的核心感測器─光達（Lidar）為研究對象。本研究將使用情境分析法（Scenario Analysis）設定出不同的變項，以建立不同的情境加以分析，根據專利探勘並確認選擇檢索的專利數據資料庫（美國專利商標局USPTO），然後根據專利檢索結果來建構技術功效矩陣，畫出專利地圖。透過專利地圖結合灰關聯以及VIKOR方法找出關鍵發展技術，並依據不同的情境找出適合該技術之開放式創新或改善策略。

With the development of science and technology, transportation tech-nology has become increasingly innovative, and the technology of driverless cars has emerged. The development of related technologies for unmanned ve-hicles is likely to greatly improve safety, help reduce traffic congestion, and provide more driving options. With companies such as Google and Tesla launching unmanned vehicles and testing on the road many times, it has also affected the layout or R&D strategies of other players. This study analyzes the core sensor of the unmanned vehicle, Lidar, as the research object. This study will use Scenario Analysis to set up different variables to establish different scenarios for analysis, based on patent mining and confirm the selection re-sults of the USPTO. The result is to construct a technical matrix and draw a patent map. Identify key development techniques through patent maps com-bined with grey relation analysis and VIKOR methods, and identify open in-novations or improvement strategies appropriate to the technology based on different scenarios.