Journal of Urban Management最新文献_第7页

Simulation-based evaluation of the impact of civic literacy on participatory urban planning: A study of introducing Shared Autonomous Vehicles 公民素养对参与式城市规划影响的模拟评估：引入共享自动驾驶汽车的研究

IF 5 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2025-09-01 Epub Date: 2025-02-19 DOI: 10.1016/j.jum.2025.02.001

Shiyuan Wang, Kazuo Hiekata, Takuya Nakashima

As participatory urban planning has gained traction recently, the consensus-building process among citizens has become crucial to its success. In particular, the level of understanding among citizens regarding new technologies or systems in the city, referred to as civic literacy in this study, can significantly impact the quality and speed of consensus building. While frameworks exist to replicate this consensus-building process, no research has considered differences in civic literacy or applied them to participatory urban planning issues. This study proposes a simulation-based method to quantitatively evaluate how civic literacy influences the consensus-building process for new policies. Consensus building process of the introduction of Shared Autonomous Vehicles (SAVs) was examined as a case study. The python-based multi-agent simulator was built based on the group decision making framework combining with the level of understanding among citizen stakeholders which is represented by two factors: utility bias from true values and their variance (degree of uncertainty) regarding the benefits of SAVs. Through Monte Carlo simulations with several conditions, we observed significant variations in the patterns of change in both the speed and quality of the consensus-building process due to differences in initial values. For instance, changing the information level can, in some cases, more than double the time required for consensus. This effect varies greatly depending on the rigor of the consensus and the strength of the bias.

由于参与式城市规划最近获得了牵引力，在公民之间建立共识的过程已成为其成功的关键。特别是，市民对城市新技术或新系统的理解水平，在本研究中被称为公民素养，可以显著影响共识建立的质量和速度。虽然存在复制这一建立共识过程的框架，但没有研究考虑到公民素养的差异或将其应用于参与性城市规划问题。本研究提出了一种基于模拟的方法来定量评估公民素养如何影响新政策的共识建立过程。以共享自动驾驶汽车（sav）引入的共识构建过程为例进行了研究。基于python的多智能体模拟器基于群体决策框架，结合公民利益相关者之间的理解水平，由两个因素表示：真实值的效用偏差和他们对SAVs收益的方差（不确定性程度）。通过蒙特卡罗模拟几种条件，我们观察到由于初始值的差异，共识建立过程的速度和质量的变化模式存在显著差异。例如，在某些情况下，改变信息级别可能会使达成共识所需的时间增加一倍以上。这种影响因共识的严谨性和偏见的强度而有很大差异。

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引用次数: 0

Assessment for promoting on campus disaster management: Experience of new Taipei city 促进校园灾害管理之评估：新北市之经验

IF 5 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2025-09-01 Epub Date: 2025-03-05 DOI: 10.1016/j.jum.2025.02.005

Kuo-Chen Ma , Mo-Hsiung Chuang , Yung-Fang Chen

Natural disasters become frequently in New Taipei City due to climate change and its geographical location and consequently result in heavy losses to the city's properties in recent years. Disaster management education funds were provided by the government to improve resilience to disasters.

This study has developed an evaluation and interaction model to promote campus disaster management based on the method of semi-structured interview with an evaluation table for self-evaluation and expert evaluation systems. The evaluation table have 5 major assessment items with a total score of 100%. The assessment items with different scores given in the parenthesis are organizational planning and campaigning (20%), education and activities for disaster prevention (28%), utilization of disaster prevention tools and equipment (20%), prevention drills (25%), and innovation and performance (7%). Each item has 5 performance indicators with scores dependent on their relative importance.

Eighteen schools identified as high disaster risk schools were selected to conduct the self-evaluation and expert evaluation in New Taipei City. Both evaluation results were displayed in radar charts for visual comparison and analyzed using SWOT analysis. The analyzed results provide useful information for understanding the strong and weak points in the present work of school disaster management in New Taipei City and for improving the management work in the future.

近年来，新北市受气候变迁及地理位置等因素影响，自然灾害频发，造成重大财产损失。政府提供灾害管理教育资金，以提高抗灾能力。本研究基于半结构化访谈法、自评表法和专家评价系统，构建了促进校园灾害管理的评价与互动模型。评价表有5个主要评估项目，总分为100%。括号中分数不同的评估项目分别是：组织策划和宣传（20%）、防灾教育和活动（28%）、防灾工具和设备的使用（20%）、防灾演练（25%）、创新和绩效（7%）。每个项目有5个性能指标，得分取决于它们的相对重要性。选取18所高灾害风险学校，在新北市进行自评与专家评鉴。两种评价结果以雷达图的形式进行直观对比，并采用SWOT分析法进行分析。分析结果对了解新北市目前学校灾害管理工作的优缺点，以及未来改善学校灾害管理工作提供有用的资讯。

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引用次数: 0

Mapping cultural heritage sites at risk: A support tool for heritage sites management 绘制濒危文化遗产地：遗产地管理的辅助工具

IF 5 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2025-09-01 Epub Date: 2025-01-24 DOI: 10.1016/j.jum.2025.01.007

Maria Giovanna Brandano , Chiara Conti , Marco Modica , Giulia Urso

Under the threat of climate change, the world has become increasingly unsafe, with extreme weather events causing devastation and high economic costs. These impacts are heterogeneous because of the interaction between different regional climate changes and the varying socio-economic characteristics of affected places. Climate change also impacts the management of cultural heritage sites. We then propose a method to identify heritage sites at risk from climate change issues, considering the single components of risk, namely both the natural hazard and the resilient/vulnerable local characteristics that may increase or mitigate the potential damage. The link between the natural and human spheres is, in fact, crucial for the development of suitable mitigation and prevention strategies, particularly relevant for developing countries that suffer from scarce economic resources. Overall, this work aims to provide a method to detect heritage sites at risk and a decision support tool for strategically managing cultural sites. We focus on Italy since it is one of the countries with a higher endowment of cultural heritage. However, thanks to its high replicability, this tool might be exported and adopted in different contexts and scenarios.

在气候变化的威胁下，世界变得越来越不安全，极端天气事件造成破坏和高昂的经济成本。由于不同区域气候变化和受影响地区不同社会经济特征之间的相互作用，这些影响具有异质性。气候变化也影响着文化遗产地的管理。然后，我们提出了一种方法来识别受气候变化问题威胁的遗产地，考虑风险的单一组成部分，即自然灾害和可能增加或减轻潜在损害的弹性/脆弱的当地特征。事实上，自然领域和人类领域之间的联系对于制定适当的缓解和预防战略至关重要，这对经济资源匮乏的发展中国家尤其重要。总的来说，这项工作旨在提供一种方法来检测处于危险中的文化遗址，并为文化遗址的战略管理提供决策支持工具。我们关注意大利，因为它是文化遗产禀赋较高的国家之一。然而，由于其高可复制性，该工具可以导出并在不同的上下文中和场景中采用。

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引用次数: 0

Synergizing urban and mobility governance: Insights from Dubai and Lahore 协同城市和交通治理：来自迪拜和拉合尔的见解

IF 5 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2025-09-01 Epub Date: 2025-03-07 DOI: 10.1016/j.jum.2025.02.009

Abdul Ghaffar Chaudhry , Houshmand Masoumi , Hans-Liudger Dienel

Urban centers in the Middle East and North Africa (MENA) and South Asian (SA) regions face challenges like urban sprawl, low-density development, and heavy investment in road infrastructure, worsened by fragmented governance and political instability. This study adopts a qualitative approach, utilizing semi-structured interviews with decision-makers in Dubai and Lahore, to identify and analyze key factors influencing urban management and mobility governance. Grounded theory is applied to compare the distinct governance challenges, policy priorities, and strategic planning approaches of the two cities. Key findings show that that Dubai immensely benefits from effective decision-making, a clear strategic vision, long-term transport planning, and structured program implementation. In contrast, Lahore grapples with overlapping roles among multiple planning agencies, delays in Master Plan approvals, and weak implementation frameworks, all of which contribute to uncontrolled horizontal expansion and a road-centric development model. This paper advances the urban governance literature by proposing a conceptual governance framework and a maturity model offering actionable insights for developing cities striving for more sustainable and equitable urban mobility.

中东和北非（MENA）和南亚（SA）地区的城市中心面临着城市扩张、低密度发展和道路基础设施大量投资等挑战，而治理碎片化和政治不稳定又加剧了这些挑战。本研究采用定性方法，利用对迪拜和拉合尔决策者的半结构化访谈，确定和分析影响城市管理和交通治理的关键因素。运用扎根理论比较两个城市不同的治理挑战、政策重点和战略规划方法。主要研究结果表明，迪拜从有效的决策、清晰的战略愿景、长期的交通规划和结构化的项目实施中受益匪浅。相比之下，拉合尔面临着多个规划机构角色重叠、总体规划审批延迟以及实施框架薄弱等问题，所有这些都导致了不受控制的横向扩张和以道路为中心的发展模式。本文通过提出概念性治理框架和成熟度模型来推进城市治理文献，为发展中城市争取更可持续和公平的城市流动性提供了可操作的见解。

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引用次数: 0

How far and discernible are public toilets? A city-scale study using spatial analytics and deep learning in Nanjing, China 公共厕所有多远，有多容易辨认？基于空间分析和深度学习的南京城市尺度研究

IF 5 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2025-09-01 Epub Date: 2025-02-08 DOI: 10.1016/j.jum.2025.01.011

Yue Dai, Lifei Wang, Zhen Xu, Mingyu Li

Everyone needs access to public toilets, yet despite their importance in ensuring timely use, the shortage and limited availability of public toilets remain a global challenge. Conventional assessments of public toilet services often overlook actual usage patterns and focus solely on physical distance, neglecting wayfinding convenience in shaping user experience. This study addresses these gaps by conducting a city-wide analysis of public toilet service efficiency in Nanjing, China, emphasizing both accessibility and wayfinding. An online route planning algorithm was employed to generate a 5-, 10-, and 15-min catchment area map, quantifying the spatial coverage of public toilets. Additionally, deep learning techniques were utilized to detect public toilet signage in Nanjing's old urban area street views to assess wayfinding convenience. The results indicate an average toilet density of 0.91 units per km², with 10-min catchment areas covering 27.47% of the city space, 71.36% of the population, and 82.00% of public service points of interest in Nanjing. However, signage is present at only 38.32% of public toilets within the old urban area, revealing disparities in distribution, coverage gaps, and inadequate signage in certain areas. To address these gaps, Nanjing could expand public toilet facilities to enlarge the 10-min catchment areas and encourage more businesses to open their toilets to the public. Additionally, increasing signage, including for social public toilets, could improve wayfinding and thus enhance the service efficiency of public toilets across the city. This study offers actionable insights for urban planners and policymakers to improve public toilet infrastructure. Moreover, the methodology provides a scalable framework for evaluating urban infrastructure in cities worldwide.

每个人都需要使用公厕，然而，尽管公厕在确保及时使用方面很重要，但公厕短缺和可用性有限仍然是一个全球性挑战。对公共厕所服务的传统评估往往忽视了实际的使用模式，只关注物理距离，忽视了在塑造用户体验方面的寻路便利性。本研究通过对中国南京全市公共厕所服务效率进行分析，强调可达性和寻路性，解决了这些差距。采用在线路线规划算法生成5分钟、10分钟和15分钟集水区地图，量化公厕的空间覆盖范围。此外，深度学习技术被用于检测南京老城区街景中的公共厕所标志，以评估寻路便利性。结果表明，南京平均厕所密度为0.91个/ km2, 10分钟集水区面积占城市空间的27.47%，人口的71.36%，公共服务兴趣点的82.00%。然而，在旧城区，只有38.32%的公厕安装了标识，这表明在分布上存在差异，覆盖范围存在差距，某些地区标识不足。为了解决这些问题，南京可以扩大公共厕所设施，扩大10分钟的集水区，并鼓励更多企业向公众开放厕所。此外，增加标识，包括社会公厕的标识，可以改善寻路，从而提高整个城市公厕的服务效率。本研究为城市规划者和政策制定者改善公共厕所基础设施提供了可操作的见解。此外，该方法为评估全球城市的城市基础设施提供了一个可扩展的框架。

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引用次数: 0

Using system dynamics to inform scenario planning: Application to the Souss-Massa basin, Morocco 利用系统动力学为情景规划提供信息：在摩洛哥Souss-Massa盆地的应用

IF 5 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2025-09-01 Epub Date: 2025-02-13 DOI: 10.1016/j.jum.2025.01.012

Ayoub Guemouria , Abdelghani Chehbouni , Salwa Belaqziz , Driss Dhiba , Lhoussaine Bouchaou

The watershed represents a holistic system whose poor understanding of its multiple subsystems can lead to a pronounced water scarcity. This study aims to develop an innovative technique for managing water resources within the Souss-Massa watershed. It uses the System Dynamics (SD) methodology to analyze the interplay among the factors involved in water supply and demand. The results show that under the Business As Usual (BAU) scenario, water sustainability in this watershed is not assured. Groundwater drawdown (GWD) will increase significantly, with an estimated average decrease of −337 Mm³ for the period 2022 to 2050. To remedy this critical situation, several simulations were developed, each representing a distinct scenario. Scenario 1 improves irrigation efficiency by 10%, while scenario 2 achieves a 20% improvement. Scenario 3 builds on scenario 2 by doubling the volume of reused water. Scenario 4 extends scenario 3 by also doubling the volume of desalinated water. Scenario 5 combines the 10% improvement in irrigation efficiency from scenario 1 with a doubling of both reused and desalinated water volumes, along with a stabilization of irrigated areas. Scenario 6 adds a 7% increase in water supply to the measures in scenario 5. Finally, scenario 7 combines the 10% irrigation efficiency improvement from scenario 1 with a doubling of reused and desalinated water volumes, but reduces the irrigated area by 15%. This study is of crucial importance to decision-makers, as it provides them with strategies for promoting water-saving practices and, consequently, advancing the sustainable development agenda.

流域代表了一个整体系统，对其多个子系统的理解不足可能导致明显的水资源短缺。本研究旨在开发一种管理苏萨-马萨流域水资源的创新技术。它使用系统动力学（SD）方法来分析涉及供水和需求的因素之间的相互作用。结果表明，在“一切照旧”情景下，该流域的水资源可持续性得不到保证。地下水降水（GWD）将显著增加，预计2022年至2050年期间平均减少- 337 Mm3。为了纠正这种危急情况，开发了几个模拟，每个模拟代表一个不同的场景。情景1将灌溉效率提高10%，而情景2将提高20%。方案3建立在方案2的基础上，将回用水量增加一倍。方案4扩展方案3，也将淡化水的体积增加一倍。方案5与方案1相比，灌溉效率提高了10%，重复用水和脱盐水量增加了一倍，灌溉面积也稳定了下来。在方案5的措施基础上，方案6增加了7%的供水。最后，方案7结合了方案1中10%的灌溉效率提高，再利用和脱盐水量增加了一倍，但灌溉面积减少了15%。这项研究对决策者至关重要，因为它为他们提供了促进节水做法，从而推进可持续发展议程的战略。

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引用次数: 0

Integrated territorial planning and digital innovation for climate-resilient urbanization in developing countries 发展中国家气候适应型城市化的综合国土规划和数字创新

IF 5 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2025-09-01 Epub Date: 2025-06-02 DOI: 10.1016/j.jum.2025.05.010

Hassan Radoine, Kh Md Nahiduzzaman

引用次数: 0

A capability maturity model for smart city process-aware digital transformation 面向智慧城市过程感知数字化转型的能力成熟度模型

IF 5 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2025-09-01 Epub Date: 2025-03-19 DOI: 10.1016/j.jum.2025.03.001

Shohreh Ajoudanian , Hamid Reza Aboutalebi

Smart cities are constructed and developed by governmental bodies and urban leaders capable of digital transformation. This modification aims to mitigate urban challenges while fostering robust urban growth using advanced technologies. However, many existing maturity models fail to adequately address the specific requirements and gaps in digital transformation capabilities necessary for effective urban management. The implementation of information and innovative communication strategies in urban areas has led to the development of new organizational procedures and business models. City managers recognize that digital transformation can drive urban growth. Therefore, they can enhance their processes by following a clear strategy outlined in a digital transformation capability maturity model. Despite the growing emphasis on digital transformation in urban management, existing maturity models do not adequately capture the specific processes and requirements necessary for effective implementation, resulting in challenges for city managers in assessing their capabilities. For this purpose, this study evaluates smart city maturity models and identifies gaps in the requirements for digital transformation capability. As a result, an innovative model for assessing the maturity of digital transformation capability in smart cities is proposed. The presented maturity model is particularly helpful for businesses and private companies seeking to embrace digital transformation for urban growth. It facilitates their systematic advancement toward higher maturity levels by enabling them to assess current capabilities. The majority of assessors are either very satisfied or satisfied with the criteria, according to the SC-DT-CMM evaluation results.

智慧城市是由具备数字化转型能力的政府机构和城市领导者建设和发展的。这一修改旨在缓解城市挑战，同时利用先进技术促进强劲的城市增长。然而，许多现有的成熟度模型未能充分解决有效城市管理所需的数字化转型能力的具体要求和差距。在城市地区实施信息和创新沟通战略导致了新的组织程序和商业模式的发展。城市管理者认识到数字化转型可以推动城市发展。因此，他们可以通过遵循数字转换能力成熟度模型中概述的清晰策略来增强他们的流程。尽管越来越重视城市管理的数字化转型，但现有的成熟度模型并不能充分捕捉有效实施所需的具体流程和要求，这给城市管理者评估其能力带来了挑战。为此，本研究评估了智慧城市成熟度模型，并确定了数字化转型能力需求方面的差距。因此，本文提出了一种评估智慧城市数字化转型能力成熟度的创新模型。所提出的成熟度模型对寻求通过数字化转型促进城市增长的企业和私营公司特别有帮助。它使他们能够评估当前的能力，从而促进他们系统地向更高的成熟度水平发展。根据SC-DT-CMM的评估结果，大多数评估者要么非常满意，要么对标准感到满意。

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引用次数: 0

Analysis of urban functional areas based on graph clustering neural networks 基于图聚类神经网络的城市功能区分析

IF 5 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2025-09-01 Epub Date: 2025-01-27 DOI: 10.1016/j.jum.2025.01.003

Huimin Bai, Xia Zhu, Yuanping Liu, Tiange Zhang, Cui Jia, Jie Cao, Hao Zhang, Xinran Liu

Urban functional areas, as an important fundamental component of urban planning, hold significant importance for optimizing urban layouts, resource allocation, and the rational organization of socio-economic activities. Urban functional area division using traditional methods often has limitations, such as relying on a single data source and using division methods that are mostly based on road network units. To address these issues, this paper considers the impacts of Open Street Map road network data, Point of Interest data, nighttime light data, and land use data on functional area identification and proposes a method based on Graph Clustering Neural Networks to analyze and study urban functional areas. To begin with, the basic datasets are utilized to extract the spatial structure and attribute features of urban functional areas. Then, a transportation network model is constructed by combining the basic characteristics of the road network with socio-economic characteristics. Through the use of Graph Clustering Neural Networks and clustering algorithms, urban functional areas can be identified through clustering through the integration of Graph Neural Networks and clustering algorithms. For functional area analysis, Point of Interest data and land use data are then utilized. Finally, the accuracy of the clustering results is verified by comparison with real images. Beijing was chosen as the study area for this research. The Graph Clustering Neural Network model's urban functional area analysis is highly accurate, allowing for precise identification of the city's spatial distribution characteristics, as demonstrated by the results. The analysis of functional areas offers a better understanding of urban characteristics and distribution patterns, providing more scientific and precise references for urban planning. Additionally, it offers strong support for real-world urban management and decision-making, such as traffic planning, land use optimization, and public resource allocation.

城市功能区作为城市规划的重要基础组成部分，对优化城市布局、优化资源配置、合理组织社会经济活动具有重要意义。传统的城市功能区划分方法往往存在依赖单一数据源、多基于路网单元的划分方法等局限性。针对这些问题，本文考虑了开放街道地图路网数据、兴趣点数据、夜间灯光数据和土地利用数据对功能区识别的影响，提出了一种基于图聚类神经网络的城市功能区分析研究方法。首先，利用基础数据集提取城市功能区的空间结构和属性特征。然后将路网的基本特征与社会经济特征相结合，构建交通网络模型。通过使用图聚类神经网络和聚类算法，通过图神经网络和聚类算法的融合，可以通过聚类来识别城市功能区。对于功能区分析，然后使用兴趣点数据和土地利用数据。最后，通过与真实图像的对比，验证了聚类结果的准确性。本研究选择北京作为研究区域。结果表明，图聚类神经网络模型的城市功能区分析非常准确，可以精确识别城市的空间分布特征。功能区分析有助于更好地了解城市特征和分布格局，为城市规划提供更科学、更精确的参考。此外，它还为现实世界的城市管理和决策提供强有力的支持，如交通规划、土地利用优化和公共资源配置。

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引用次数: 0

Leveraging machine learning to predict traffic jams: Case study of Casablanca, Morocco 利用机器学习预测交通堵塞：以摩洛哥卡萨布兰卡为例

IF 5 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2025-09-01 Epub Date: 2025-03-04 DOI: 10.1016/j.jum.2025.02.004

Laaziza Hammoumi, Saad Farah, Mohamed Benayad, Mehdi Maanan, Hassan Rhinane

Traffic congestion in urban centers not only hampers mobility but also significantly impacts economic activities and environmental sustainability. This study leverages advanced machine learning techniques to analyze and predict traffic jams, utilizing a detailed dataset of 9847 recorded accident pixels from Waze, a popular navigation platform that aggregates real-time and historical traffic data from millions of users. The study is centered on Casablanca, Morocco and serves as a critical case study for urban traffic management. Advanced algorithms including Random Forest (RF), K-Nearest Neighbors (KNN), XGBoost, and Artificial Neural Network (ANN) were evaluated for their effectiveness in congestion prediction. The Random Forest model demonstrated exceptional performance with an accuracy of 96% and an AUC of 0.997, effectively distinguishing between congested and non-congested states. In contrast, the ANN displayed a lower performance with an accuracy of 64% and an AUC of 0.5, indicating challenges in handling complex traffic patterns. These findings underscore the potential of tailored machine learning solutions to enhance urban traffic management and planning, offering a foundation for deploying intelligent traffic systems that could significantly alleviate congestion in major urban areas.

城市中心的交通拥堵不仅阻碍了人们的出行，而且严重影响了经济活动和环境的可持续性。这项研究利用先进的机器学习技术来分析和预测交通拥堵，利用来自Waze的9847个记录事故像素的详细数据集，Waze是一个流行的导航平台，汇集了数百万用户的实时和历史交通数据。该研究以摩洛哥卡萨布兰卡为中心，是城市交通管理的重要案例研究。对随机森林（RF）、k近邻（KNN）、XGBoost和人工神经网络（ANN）等先进算法在拥塞预测中的有效性进行了评估。随机森林模型表现出优异的性能，准确率为96%，AUC为0.997，有效区分了拥塞和非拥塞状态。相比之下，人工神经网络显示出较低的性能，准确率为64%，AUC为0.5，这表明在处理复杂的交通模式方面存在挑战。这些发现强调了量身定制的机器学习解决方案在加强城市交通管理和规划方面的潜力，为部署智能交通系统提供了基础，可以显著缓解主要城市地区的拥堵。

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引用次数: 0