不同運輸方式間正義的都市道路空間重分配－以台北市為例

Abstract

本研究旨在對台北都會區五種運輸方式（行人、自行車、公車、機車、汽車）的道路路權與空間分佈，提出一套重新分配道路空間以促進正義發展的方法。此項議題的重要性在既有城市的主要道路路權分配中，較缺少對除汽車之外對運輸方式路權分配的關注，因此有必要以修正正義的概念，設計一系列對不同運輸方式的空間重分配方法。 這套空間重分配的方法基礎為約翰‧羅爾斯(John Rawls)的“正義論(A Theory of Justice)”，作為最佳化目標函數的理論基礎。以既有空間分配、既有路段車流量、基礎設施、綠地面積、環境條件等諸多因素，引用相關文獻並用作設計模型的正義標準。資料來源提取自專家問卷所提供的數值，與現有各來源的統計資料兩種，將其利用分析網絡程序（Analytical Network Process, ANP）以評估不同運輸方式的正義相對重要性，以此作為目標式中運輸方式正義的空間比例基準。隨後利用最佳化模型，按既有的旅運習慣與道路設計作為限制式，最終可得出實際可行的道路斷面配置建議，並進行相關討論。 這項研究的主要貢獻在於試圖將定性的正義理論，與定量的數學規劃模型結合，從而提供一套包含多元正義觀點的道路空間重分配模型。在空間有限的城市建成區主要道路範圍內，使各運輸方式的使用者都能趨向於正義的道路空間分配結果，最終實現交通平權的社會觀念。

This study investigates five transportation modes (pedestrians, bicycles, buses, motorcycles, cars) in the Taipei Metropolitan Area, where the allocation of right-of-way on major roads lacks attention to the transportation modes other than cars, especially to the two wheelers. Therefore, it is necessary to design a series of spatial redistribution model for different transportation modes based on the concept of revised justice. It proposes a method for equitably reallocating road space to promote just development. The theoretical foundation of this research rests upon John Rawls' "A Theory of Justice," serving as the basis for the optimization objective function. Various criteria, including existing space allocation, traffic volume on road segments, infrastructure, green space availability, and other factors, are employed as constraints and criteria for the design model. Data from expert surveys and existing sources are utilized to inform these criteria, while the Analytical Network Process (ANP) is employed to assess the relative importance of different modes. Each mode is integrated into an Injustice Index developed within this research framework. The optimal model is subsequently utilized to propose recommendations for allocating road cross-section configurations, offering practical suggestions for implementation. The primary contribution of this study lies in its attempt to amalgamate qualitative theoretical principles with quantitative mathematical programming models, thereby furnishing a suite of road right-of-way reallocation models that embrace diverse perspectives of equality. Within the confines of limited urban road space, users of each transportation mode can strive to achieve a fairer distribution of road space, ultimately attaining their notions of "justice" regarding right-of-way.