得益於資訊科技及數據分析技術之精進，以及電腦運算速度的提升，公共運輸路網規劃已能借助多種新興資料源進行剖析與探討。典型的公共運輸路網規劃需要藉助大量的家戶旅次調查活動，才能取得足夠的數據基礎，以便做預測、路網指派與評估。近年來因巨量資料（如：手機信令資料、GIS資料或電子票證資料）足以描繪接近母體行為態樣，對於針對焦點客群進行產品服務的改造與設計極有助益，故應用新興的巨量資料用以剖析用戶行為已然蔚為風潮，並有多篇研究試圖藉由巨量資料探討運輸服務、覆蓋率、路網規劃、永續運輸等面向。
遵循典型的交通規劃四步驟，並基於同一筆資料對同一場域進行公車路線規劃，不同的規劃者有不同的路網方案。每種路線方案皆有其思維脈絡，且各有其設計邏輯。然而，根據有限理性決策（Limited Decision Making）觀點，決策者無法做到完全理性的決策，只能追求滿足基本條件的決策方案，而非最理性的最佳化決策。因此，必須建構一套量化指標，協助決策者進行理性思考，並追求更佳的路網方案。
量化評估指標雖有助於決策者思考，但過度偏重單一指標，或者無視指標之輕重高低之別，則容易造成更大的問題。甚至過度聚焦於公車運輸系統之指標，專注於提高公車營運內部效率（Efficiency is doing things right），卻忽略達成國家或城市永續發展之外部整體效益（Effectiveness is doing the right things）。例如：過度偏重覆蓋率指標，雖然可使民眾可就近取用公車，期許民眾提高搭乘意願。但政府財源有限的情況下，則可能導致其他路線減班營運，導致班距拉長，反而讓民眾不耐久候而降低搭乘意願。
因此，本研究根據文獻回顧，藉由解構旅次鏈，探索各旅次中隱含之關鍵要素，以覆蓋性、易行性、連接性作為公車系統內部效率層面之指標。此外，引用永續運輸相關文獻之研究，以經濟面、社會面及環境面作為公車系統外部效益層面之指標。與此同時，藉由文獻回顧一併確認六大指標及其計算方式。
本研究採用ANP之研究架構，設計問卷並蒐集產、官、學三方之專家意見，經由ANP分析確認各指標之權重，再用以實際評估臺南市區公車路線現況及調整方案之結果。
研究結果發現，整合系統內、外部六大指標並確立指標間之權重關係，並透過公車路線永續營運指數（Sustainable Operation of Bus Route Index）確實可用於評估兩個以上之路網方案，不僅可以宏觀角度檢視整體路網之情形，更可針對個別路線進行六個維度的評比，篩選出更符合民眾需求的路網方案。

Owing to the innovation of big data analytics, planners can grasp residents' daily movements completely and design bus networks efficiently. Moreover, residents offer many thoughts about adjusting bus routes and consequently planners or public transportation service operation agencies need to find a balance between supply and demand within limited governmental budget. In order to seek suitable bus routes that meet demand and supply. So that planners and decision-makers need some quantitative indicators to assess and select the better network design.
Previous studies focused on transit systems or sustainable transportation independently, and fewer studies integrate indicators from both areas. this study integrates two aspects of internal and external, while developing six indicators for evaluating network.
A conceptual model is built to describe these interrelated indicators in practice. In order to analyze the weights of each indicator, this study designed a questionnaire according to the ANP research methodology, and obtained input from industry, government and scholars. While assessing current and recommended networks in Tainan, the empirical results demonstrate that 15 routes in the recommended network design are better than current network, accounting for 71.43% of the overall design.
This study improves the assessing viewpoints of bus network design, including macro and micro aspects of method. Also, providing new quantitative indicators for planners, public transportation service operation agencies and decision-makers, when they want to choose a suitable network design that meets people's daily travel demand.

一、中文文獻
中央研究院人社中心地理資訊科學研究專題中心（2014）。 Quantum GIS 操作手冊。檢自：http://gis.rchss.sinica.edu.tw/qgis/wp-content/uploads/2015/09/QGIS2.2_Handout_20140619.pdf
內政部營建署（2003）。 高齡者日常活動步道系統規劃。
交通部統計處（2016）。 105年民眾日常使用運具狀況調查交叉統計表。
交通部統計處（2020）。 109年民眾日常使用運具狀況調查交叉統計表。
交通部運輸研究所（2019a）。 Koinonia: 交通就是感動 : 2020運輸政策白皮書。臺北：交通部。
交通部運輸研究所（2019b）。公共運輸縫隙掃描決策支援系統之整合及推廣運用。 臺北：交通部。
朱宏祥（1995）。臺北市棋盤式公車路網與現況公車路網之效益評估比較。國立交通大學交通運輸研究所碩士論文。
李泓儒（2018）。利用信令資料推估軌道運具旅運起訖之研究。國立交通大學運輸與物流管理研究所碩士論文。
周依潔（2008）。高齡者日常活動步道系統規劃。國立交通大學交通運輸研究所碩士論文。
周易陵、陳則銘、鄭書恆 （2020）。 手機信令應用於捷運路網規劃。中興工程， 146，頁 65-71。
邵珮琪（2013）。 臺灣航空器事故模型分析暨機場安全管理系統績效評估。 國立成功大學交通管理科學系博士論文。
施鴻志、段良雄、凌瑞賢（1984）。都市交通計畫的理論與實務（第十一版）。臺北：茂昌圖書。
洪琮博（2017）。利用手機信令推估旅運起迄矩陣。國立交通大學交通運輸研究所碩士論文。
張有恆（2005）。現代運輸學。臺北：華泰文化。
張有恆（2013）。現代運輸學（第三版）。臺北：華泰文化。
馮正民、朱宏祥（1997）。 台北市棋盤式公車路網與現況公車路網之效益評估比較。運輸學刊， 10（1），頁 119-140。
黃宇晨、林谷鴻（2011）。 使用分析網路程序法（ANP）評估招募目標的關鍵準則－以 Y 公司為例。工程科技與教育學刊， 8（3），頁502-517。
臺南市政府（未出版）。 大臺南公車系統整合規劃案。
臺南市政府資料開放平台 （2021）。 大台南公車運量資訊（2014-2020） 。檢自：https://data.tainan.gov.tw/dataset/bus-ridership
褚志鵬 （2003）。 Analytic Hierarchy Process Theory 層級分析法 AHP。檢自：http://web.ntust.edu.tw/~vincent/dape/AHP_Tutorial_Chu
鄭永祥（2009）。網路分析程序法之理論與應用。國防管理學報， 30（2），頁69-79。
魏健宏、邱馳（2020）。以覆蓋率、彎繞度及連接性探討公車路網之服務水準─以台南市公車為例。「中華民國運輸學會109年學術論文研討會」發表之論文， 臺南。
 
二、英文文獻
Allard, R. F., and Moura, F. （2015）. The Incorporation of Passenger Connectivity and Intermodal Considerations in Intercity Transport Planning. Transport Reviews, 36, 1-27.
Arnone, M., Delmastro, T., Giacosa, G., Paoletti, M., and Villat, P. （2016）. The potential of e-ticketing for public transport planning: the Piedmont region case study. Transportation Research Procedia, 18, 3-10.
Caggiani, L., and Camporeale, R. （2021）. Accessibility indicators for fair bike-sharing systems based on level of service. Paper presented at the 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe, Bari, Italy.
Chakhtoura, C., and Pojani, D. （2016）. Indicator-based evaluation of sustainable transport plans: A framework for Paris and other large cities. Transport Policy, 50, 15-28.
Chen, L.-K., Woo, J., Assantachai, P., Auyeung, T.-W., Chou, M.-Y., Iijima, K., . . . Arai, H. （2020）. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. Journal of the American Medical Directors Association, 21（3）, 300-307.
Cheng, Y.-H., and Chen, S.-Y. （2015）. Perceived accessibility, mobility, and connectivity of public transportation systems. Transportation Research Part A, 77, 385-403.
Corazza, M. V., and Favaretto, N. （2019）. A Methodology to Evaluate Accessibility to Bus Stops as a Contribution to Improve Sustainability in Urban Mobility. Sustainability, 11（3）, 803. Retrieved from https://www.mdpi.com/2071-1050/11/3/803
Coxon, S., Napper, R., and Richardson, M. （2019）. Urban Mobility Design. Cambridge, United States: Elsevier.
Currie, G., and Wallis, I. （2008）. Effective ways to grow urban bus markets – a synthesis of evidence. Journal of Transport Geography, 16, 419-429.
Dancey, C. P., and Reidy, J. （2017）. Statistics without Maths for Psychology （Seventh edition ed.）. New York: Pearson.
Dobranskyte-Niskota, A., Perujo, A., and Jensen, J. J. a. P. （2009）. Indicators to Assess Sustainability of Transport Activities - Part 2: Measurement and Evaluation of Transport Sustainability Performance in the EU27. Luxembourg: European Commission
European Union Council of Ministers of Transport. （2001）. Strategy for integrating environment and sustainable development into the transport policy – Council Resolution-2340th Council meeting. Presse 131. Nr. 7587/01. Luxembourg
Guo Qiu, R. S., Shiwei He, Wangtu Xu , and Min Jiang. （2019）. Clustering passenger trip data for the potential passenger investigation and line design of customized commuter bus. IEEE Transactions on Intellogent Transportation Systems, 20（9）, 3351-3360. Retrieved from <Go to ISI>://WOS:000484207200014
Hadjidimitriou, N. S., Lippi, M., and Mamei, M. （2021）. A Data Driven Approach to Match Demand and Supply for Public Transport Planning. IEEE Transactions on Intellogent Transportation Systems, 22（10）, 6384-6394.
Irawan, M. Z., Bastarianto, F. F., Rizki, M., Belgiawan, P. F., and Joewono, T. B. （2021）. Exploring the frequency of public transport use among adolescents: a study in Yogyakarta, Indonesia. INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION. Retrieved from <Go to ISI>://WOS:000681277100001
Jarvis, A., Reuter, H. I., Nelson, A., and Guevara, E. （2008）. Hole-filled seamless SRTM data v4. International Centre for Tropical Agriculture （CIAT）.
Kou, G., Ergu, D., Peng, Y., and Shi, Y. （2012）. Data Processing for the AHP/ANP. Berlin, Heidelberg: Springer.
Lai, Y., Xu, X., Easa, S. M., and Lian, P. （2020）. Modeling arterial signal coordination for bus priority using mobile phone GPS data. Canadian Journal of Civil Engineering, 47（9）, 1094–1104. Retrieved from <Go to ISI>://WOS:000566783300009
Lin, J., Wang, P., and Barnum, D. T. （2008）. A quality control framework for bus schedule reliability. Transportation Research Part E, 44（6）, 1086-1098. Retrieved from <Go to ISI>://WOS:000259461200009
Lin, Y.-H., Chen, H.-C., Hsu, N.-W., and Chou, P. （2021）. Using hand grip strength to detect slow walking speed in older adults: the Yilan study. BMC Geriatric, 21（1）.
Litman, T. （2003）. Measuring transportation: Traffic, mobility and accessibility. Institute of Transportation Engineers, 73（10）, 28-32.
Litman, T. （2011）. Sustainability and livability : Summary of Definitions, Goals, Objectives and Performance Indicators. Victoria Transport Policy Institute.
Litman, T. （2022）. Well Measured：Developing Indicators for Sustainable and Livable Transport Planning. Victoria Transport Policy Institute
Marletto, G., and Mameli, F. （2012）. A participative procedure to select indicators of policies for sustainable urban mobility. Outcomes of a national test. European Transport Research Review, 4, 79-89.
Mavoa, S., Witten, K., McCreanor, T., and O’Sullivan, D. （2012）. GIS based destination accessibility via public transit and walking in Auckland, New Zealand. Journal of Transport Geography, 20, 15-22.
Mohanty, S., and Pozdnukhov, A. （2020）. Dynamic Origin-Destination Demand Estimation From Link Counts, Cellular Data And Travel Time Data. Transportation Research Procedia, 48, 1722-1739.
Murray, A. T., and Wu, X. （2003）. Accessibility Tradeoffs in Public Transit Planning. Journal of Geographical Systems, 5, 93-107.
O.J.Ibarra-Rojas, F.Delgado, R.Giesen, and J.C.Muñoz. （2015）. Planning, operation, and control of bus transport systems: a literature review. Transportation Research Part B: Methodological, 77, 38-75.
OECD. （1999）. Indicators for the Integration of Environmental Concerns into Transport Policies. Organisation for Economic Co-operation and Development
Ogunkunbi, G. A., and Meszaros, F. （2022）. Identifying criteria for effective urban vehicle access regulations adoption. Environmental Sciences Europe, 34（103）. Retrieved from https://doi.org/10.1186/s12302-022-00682-4
Park, J.-S., and Gang, S.-C. （2010）. A Model for Evaluating the Connectivity of Multimodal Transit Networks. Journal of Korean Society of Transportation, 28（3）, 85-98.
Pternea, M., Kepaptsoglou, K., and Karlaftis, M. G. （2015）. Sustainable urban transit network design. Transportation Research Part A, 77, 276-291.
Reisi, M., Aye, L., Rajabifard, A., and Ngo, T. （2014）. Transport sustainability index: Melbourne case study. Ecological Indicators, 43, 288-296.
Saaty, T. L., and Vargas, L. G. （2006）. Decision Making with the Analytic Network Process. New York: Springer.
Schwedes, O., and Hoor, M. （2019）. Integrated Transport Planning: From Supply- to Demand-Oriented Planning. Considering the Benefits. Sustainability, 11（21）.
Sdoukopoulos, A., Pitsiava-Latinopoulou, M., Basbas, S., and Papaioannou, P. （2019）. Measuring progress towards transport sustainability through indicators: Analysis and metrics of the main indicator initiatives. Transportation Research Part D: Transport and Environment, 67, 316-333.
Shiau, T.-A. （2012）. Evaluating sustainable transport strategies with incomplete information for Taipei City. Transportation Research Part D, 17, 427-432.
Shiau, T.-A., and Liu, J.-S. （2013）. Developing an indicator system for local governments to evaluate transport sustainability strategies. Ecological Indicators, 34, 361-371.
Simon, H. A. （1947）. Administrative behavior : a study of decision-making processes in administrative organization （1st. ed.）. New York: Macmillan.
Trépanier, M., Chapleau, R., and Tranchan, N. （2007）. Individual trip destination estimation in a transit smart card automated fare collection system. Journal of Intelligent Transportation Systems: Technology Planning, and Operations, 11（1）, 1-14.
Victorian Auditor-General’s Office. （2021）. Integrated Transport Planning. Victorian, Australia: VICTORIAN GOVERNMENT
Wang, L.-l. （2014）. Framework for Evaluating Sustainability of Transport System in Megalopolis and its Application. Science Direct, 9, 110-116.
Wang, W., Attanucci, J. P., and Wilso, N. H. M. （2011）. Bus Passenger Origin-Destination Estimation and Related Analyses Using Automated Data Collection Systems. Journal of Public Transportation, 14（4）, 131-150.
Yu, Q., Zhang, H., Li, W., Song, X., Yang, D., and Shibasaki, R. （2020）. Mobile phone GPS data in urban customized bus: Dynamic line design and emission reduction potentials analysis. Journal of Cleaner Production, 272. Retrieved from <Go to ISI>://WOS:000570238600010