<?xml version="1.1" encoding="utf-8"?>
<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">SE</journal-id><journal-title-group><journal-title>Society and Economy</journal-title></journal-title-group><issn>2995-4959</issn><eissn>2995-4975</eissn><publisher><publisher-name>Art and Technology</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.61369/SE.2026020016</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>也门萨那市城市交通拥堵治理评估：可达性、公平性、安全性与市民满意度的作用</title><url>https://artdesignp.com/journal/SE/4/2/10.61369/SE.2026020016</url><author>SalahAl-hemyari,唐可月</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>4</volume><issue>2</issue><history><date date-type="pub"><published-time>2026-02-20</published-time></date></history><abstract>本研究整合层次分析法（AHP）与模糊综合评价法（FCE）定量模型，基于210名专家与市民受访者数据，从治理与政策效能、基础设施供给、运营效率、社会环境影响四大维度，评估也门萨那等主要城市交通拥堵治理有效性。结果显示整体绩效指数为0.56，处于中等水平，治理与政策效能（0.61）对拥堵治理影响最显著，运营效率（0.49）表现最薄弱。研究证实AHP-FCE 模型在冲突后数据匮乏环境下的评估价值，为脆弱国家城市交通治理提供可复制框架，同时强调统一治理、投资多元化与智能交通系统建设的必要性。</abstract><keywords>城市交通拥堵,治理效能,层次分析法- 模糊评估,可达性、公平性、安全性,市民满意度,也门,协作治理理论</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1] Abulibdeh, A. O. (2018). Local transportation and tourism in the MENA region. In Routledge Handbook on Tourism in the Middle East and North Africa (pp. 272-289). Routledge.[2] Al-Abed, A. (2011). Sana&amp;rsquo;a urban transformation: From walled to fragmented city. JES. Journal of Engineering Sciences, 39(4), 897-918.[3] Ali, A., Ayub, N., Shiraz, M., Ullah, N., Gani, A., &amp;amp; Qureshi, M. A. (2021). Traffic efficiency models for urban traffic management using mobile crowd sensing: A survey. Sustainability, 13(23), 13068.[4] Alonso, F., Esteban, C., Montoro, L., &amp;amp; Useche, S. A. (2017). Knowledge, perceived effectiveness and qualification of traffic rules, police supervision, sanctions and justice.Cogent social sciences, 3(1), 1393855.[5] Bahamazava, K. (2025). AI-driven scenarios for urban mobility: Quantifying the role of ODE models and scenario planning in reducing traffic congestion. Transport Economics and Management, 3, 92-103.[6] Bouckaert, G., &amp;amp; Van de Walle, S. (2003). Comparing measures of citizen trust and user satisfaction as indicators of &amp;lsquo;good governance&amp;rsquo;: Difficulties in linking trust and satisfaction indicators. International Review of Administrative Sciences, 69(3), 329-343.[7] Buyukeren, A. C., &amp;amp; Hiramatsu, T. (2016). Anti-congestion policies in cities with public transportation. Journal of Economic Geography, 16(2), 395-421.[8] Colgan, B. A. (2022). Revenue, Race, and the Potential Unintended Consequences of Traffic Enforcement Reform. NCL Rev., 101, 889.[9] Currie, G., &amp;amp; Delbosc, A. (2011). Exploring the trip chaining behaviour of public transport users in Melbourne. Transport Policy, 18(1), 204-210.[10] Dehghani, A., Alidadi, M., &amp;amp; Sharifi, A. (2022). Compact development policy and urban resilience: a critical review. Sustainability, 14(19), 11798.</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
