論文提要: 都市的宜居性與永續發展乃當前人類生活的重要課題,其中都市運輸活動與規劃更會對兩者產生顯著的影響。然而,目前大部分的規劃策略,並未考量都市發展與都市運輸需求不斷擾動的特性,同時,都市運輸決策亦未納入因隨時間變動而產生不同考量因子所產生規劃上的影響。 另一方面,由於現今社會通訊及電腦技術的普及與進步,已使我們在蒐集、儲存及處理資料的能力今非昔比,「巨量資料(Big data)」的出現,不僅使人們在分析與預測方面更加準確,其高時效性更讓我們能即時解決許多挑戰。因此,在此契機下,我國現今應用巨量資料於都市規劃、交通運輸領域的嘗試應是十分值得研究與探討的新領域。 本研究將應用巨量資料以為基礎,希望能進一步將其應用於都市永續運輸策略之研究。研究將先針對國內外相關文獻進行回顧與分析,初步歸納出符合宜居城市原則的永續運輸指標,再採用模糊德爾菲法(Fuzzy Delphi Technique, FDT)的專家問卷方式篩選出重要指標。同時,為使研究結果能實際應用於規劃決策中隨時間而可能改變之動態環境的不同策略因應,本研究將進一步結合動態網路程序法(Dynamic Network Process, DNP)及資料探勘技術(Data Mining),希能藉由分析與都市運輸相關之巨量資料以預測指標的未來動態情況,並研擬出在動態時空變化下,宜居城市永續運輸策略的優先順序評估。本研究期望能夠藉由研究成果的呈現呼應當前都市規劃的需求,並使我國的永續運輸策略有更明確的發展基礎。
Abstract: The Livability and Sustainability of city, which are the most important subject of human life, both be significantly influented by urban transportation. However, most decision making of planning didn’t consider the constantly changing nature of urban transportation and time factor. On the other hand, the popularity and advancement of communication and computer technology makes us able to process large amounts of data. The coming of “Big Data”, not only let people predict more precisely, also let us solute problem more immediately. As such, applying Big Data in Urban transportation planning should be valuable. In this study, we try to applying Big Data in Urban transportation strategy. First, we initially organize the sustainable transportation indicators that meet the principle of livable city. Second, using Fuzzy Delphi Technique to filter the most important indicators. In the end, in order to let the planning decision can consider time factor, we combine Big Data and Dynamic Network Process to assess the weight of indicators in the dynamic future. This study expects to respond to the needs of the current urban planning and sustainable transport strategy.