社區綠色交通綜合評估指標體系之研究

Abstract

因交通運輸行為所產生的環境汙染、能源消耗等問題日益嚴重，民眾開始對於這些負面效應有所反思；為了落實環境保護、資源維護，綠色交通的理念因而產生。綠色交通理念是一種全球思維，可透過在地行動，將全世界的問題轉化成日常生活之行動，藉由改善週遭的環境進而改變自身行為。社區乃是城市的基本單元，亦是多數旅次發生旅運行為的起點，其所提供的交通環境會影響運具使用。故本研究選擇以社區為單位，建立社區綠色交通綜合評估指標體系來檢視社區交通系統是否朝綠色交通方向前進。 本研究回顧國內、外綠色交通相關計畫及發展策略，經評析檢討作為本研究之理念架構。參考綠色建築及綠色社區等交通相關指標來建立初步評估指標，以運具系統：人行設施、自行車設施、捷運系統、公車系統、機車、汽車等六大構面，建立66項初擬指標。本研究利用灰色統計分析法篩選出23個指標，然因23項指標於操作上較困難，故進行二次篩選。納入最終指標體系者有14項指標：人行設施構面為人行空間連續性、人行空間有效寬度、人行空間鋪面狀況、無障礙設施、通學道；自行車設施構面為自行車道連續性、自行車道有效寬度、自行車道於路口之安全設施；捷運系統構面為捷運車站周圍之步行環境、捷運車站周圍自行車停放設施；公車系統構面：距公車站之距離、行經社區內部及周圍之公車路線數、公車為清潔能源公車、公車站周圍之步行環境；至於機車與汽車兩個構面則於篩選後完全被刪除。 在進行指標權重計算時，因捷運系統之建立，並非單一社區可進行改變，故建立兩套評估體系，分成社區中心點往外擴張一千五公尺內未有捷運系統及社區中心點往外擴張一千五公尺內有捷運系統。本研究透過專家問卷，利用模糊層級分析法進行各指標權重之求取。同時也透過專家問卷調查求取各指標之分級門檻值，採算術平均數計算在加以微調。 本研究亦針對每個指標進行詳細的定義並設立完善的調查表格，以增進調查效率。本研究以松山區及萬華區內的社區為實例應用的對象，松山區的社區乃適用社區中心點往外擴張一千五公尺內未有捷運系統的指標體系，其綠色交通綜合評估值為2.98218分，屬於C級；萬華區的社區乃適用社區中心點往外擴張一千五公尺內有捷運系統的指標體系，其綠色交通綜合評估值為1.62371分，屬於D級。本研究針對兩個社區所評估之結果，給予初步改善建議，且預估兩者改善後的綠色交通綜合評估值，松山區的社區可達3.78307分，屬於B級；萬華區的社區可達3.41907分，屬於C級。 本研究共完成兩套社區綠色交通綜合評估指標體系，包括了權重、門檻值、指標評估基準及調查表格，所建立的指標體系適用於評估社區周遭交通供給設施、服務及管理措施等，是一套易衡量、易操作的評估系統。本研究有別於以往，僅檢視單一運輸工具，本研究所構建的社區綠色交通綜合評估指標體系為評估社區整體交通系統，可以對於社區交通發展現況做評估，並具備預警、決策導引之功能。

Due to the pollution of the environment and the drainage of energy caused by transportation are getting keener and keener every day, the public began to look closer to these negative impacts. In the purpose of protecting the environment and saving resources, the concept of green transportation emerges. Green transportation is a global concept, motivated by local practices. A globalized problem is transformed into a daily action by changing the environment living around which can make us act differently. A community, the most basic unit of a city, is also the origin of most trips. The provided transportation environment would affect model selection. This research uses community as a unit to construct a green transportation index system in order to assess the transportation environment meets the goal of green transportation. This research reviews native and foreign studies about green transportation developments. After scrutinizing, these studies fit to be guides for this research. Referring to indices for green buildings and green communities, we came up with preliminary frameworks and indices: pedestrian facility, bicycle facility, MRT system, bus system, motorcycle, and automobile, in the total of 6 frameworks and the total of 66 indices under these frameworks. We applied grey statistics method to filter out the 23 more important indices. Nevertheless, 23 indices make practical operation of the index system far too complicated. Therefore, after second filtering leaves the most important 14 indices– pedestrian framework: sidewalk continuity, sidewalk available width, the quality of pavement in sidewalk, disability-free environment, commuting network in the community school children; bicycle framework: bicycle lane continuity, bicycle lane available width, bicycle lane safety measures at intersections; MRT framework: surrounding pedestrian environment for MRT stations, available bicycle parking space; bus framework: distance to bus stops, number bus routes around this community, degree of eco-friendly buses, surrounding pedestrian environment for bus stops. The motorcycle and automobile frameworks were completely ruled out after filtering.

During the calculation of weight for each index, because the construction of MRT system is beyond the reach of a community, the index system consists two sets of subsystem. One system applies to communities having MRT stations in 1500 meters from the center of the community; the other system applies to communities not having MRT stations in 1500 meters from the center of the community. This research acquires weight of each index by interviewing experts and fuzzy hierarchy analysis processing. Meanwhile interviewing experts also acquires the level gradients of each index, which will be later averaged and adjusted to reasonable values. This research also built detailed standards for evaluating each index and a table for field investigation convenience. The research includes two example communities of index system applications: the community in Song-Shan District and the community in Wan-Hua District. The community in Song-Shan District applies to the system without MRT stations within 1500 meters from the center of the community. The evaluation grade for the community in Song-Sang District is 2.98218, which is class C. On the other hand, the community in Wan-Hua District applies to the system with MRT stations within 1500 meters from the center of community. The evaluation grade for the community in Wan-Hua District is 1.62371, which is class D. After evaluating both communities, this research gives preliminary improvement suggestions which would boost both communities’ green transportation evaluation grade-- for the community in Song-Shan District is 3.78307, class B; for the community in Wang-Hua District is 3.41907, class C. Overall, this research completes a green transportation evaluation index system which includes two systems after determining the weight and standards for each index, threshold, and field investigation tables. The index system works for evaluating the transportation facilities, managements, and services surrounding communities. This system is easy to operate, and the indices are easy to evaluate. This research differs from former researches, which assess only a single transportation. The overall transportation variables in a community are taken into evaluation in the green transportation index system in order to provide assessments of current transportation development, foreseeing, and decision guidelines for a community.