Case Studies on Transport Policy最新文献_第5页

Territorial classification for mitigating socio-spatial inequalities in Fortaleza, Brazil: Advancing strategic LUTI planning towards a problem-oriented approach 缓解巴西福塔莱萨社会空间不平等的领土分类：以问题为导向的方法推进战略性城市道路交通规划

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-12-07 DOI: 10.1016/j.cstp.2025.101681

Francelino Franco Leite de Matos Sousa , Carlos Felipe Grangeiro Loureiro

Strategically assessing accessibility inequalities in urban contexts is pivotal for the sustainable land use and transportation integrated (LUTI) planning paradigm. This work introduces an innovative territorial classification methodology, focusing on problems of socio-spatial accessibility inequalities, essential for informing strategic objectives in urban planning and defining areas where policies should be prioritized to mitigate such inequalities. Applied to the city of Fortaleza, Brazil, the proposed methodology measures accessibility levels using a utility-based logsum-type indicator calculated with socioeconomic/land-use data and travel impedances from the TRANUS model simulations for past, present, and future scenarios. The findings highlight a chronic imbalance in the spatial distribution of economic activities and low-income households, alongside an increasing reliance on motorized modes for commuting. Through the hierarchization of urban space, we identify areas with potential to accommodate vulnerable populations, zones where low-income residential occupation should be discouraged due to unacceptable job accessibility conditions, and areas requiring integrated land-use and transport policies to improve access to work activities. This approach not only underscores the importance of addressing socio-spatial inequalities in LUTI planning but also provides a methodological basis for negotiating planning objectives and prioritizing critical areas across the urban territory, promoting more equitable access to opportunities.

战略性地评估城市环境中的可达性不平等对于可持续土地利用和交通一体化（LUTI）规划范式至关重要。这项工作引入了一种创新的地域分类方法，重点关注社会空间可达性不平等问题，这对于为城市规划中的战略目标提供信息和确定应优先考虑政策以减轻这种不平等的地区至关重要。该方法应用于巴西福塔莱萨市，使用基于效用的对数型指标来衡量可达性水平，该指标是根据过去、现在和未来情景的TRANUS模型模拟的社会经济/土地利用数据和旅行阻抗计算得出的。研究结果强调了经济活动和低收入家庭空间分布的长期不平衡，以及对机动交通方式的日益依赖。通过城市空间的分层，我们确定了有潜力容纳弱势群体的区域，由于不可接受的工作可达性条件而不鼓励低收入住宅占用的区域，以及需要综合土地利用和交通政策以改善工作活动的区域。这种方法不仅强调了在城市道路规划中解决社会空间不平等问题的重要性，而且还为协商规划目标和确定城市范围内关键领域的优先次序提供了方法基础，促进了更公平的机会获得。

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引用次数: 0

Flight delay prediction using machine learning and explainable AI: a case study on Hazrat Shahjalal International Airport, Dhaka 利用机器学习和可解释的人工智能进行航班延误预测：以达卡Hazrat Shahjalal国际机场为例

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-12-04 DOI: 10.1016/j.cstp.2025.101663

Fariha Tasnim Chowdhury , Sayeed Ziarat Mahmud , Syed Mohtasib Mashruk , Ahanaf Tajwar Basunia , Khan Md Hasib , Mohammad Shafiul Alam

Continuous delay in flight is a major problem for the aviation community. It results in losses, schedule adjustments, and passengers dissatisfaction. While machine learning has been used to predict delays, most earlier research focuses only on accuracy and does not explain why delays happen. This study fills that gap by combining prediction models with explainable AI (XAI) at Hazrat Shahjalal International Airport (HSIA), Dhaka. We used flight and weather data from 2022 to create a complete dataset by cleaning data, creating new features, and combining information. We tested several models including KNN, Support Vector Machine, Decision Tree, Random Forest, AdaBoost, XGBoost and CatBoost. The results show that ensemble models did the best, with CatBoost and XGBoost reaching 95% accuracy. To make these models more understandable, we used the LIME method, which showed that weather and scheduling were the main factors influencing delays. This study uniquely applies explainable machine learning to predict flight delays in a developing country context, specifically at Hazrat Shahjalal International Airport in Bangladesh. Most previous studies focused on countries like the UK, USA, Saudi Arabia, or China etc. By providing accurate predictions along with clear explanations, the results show how airlines and airport authorities can improve scheduling, better use resources, and meet international delay standards. This can help enhance passenger satisfaction and strengthen airport resilience.

航班持续延误是航空界的一个大问题。这导致了损失、时刻表调整和乘客不满。虽然机器学习已被用于预测延迟，但大多数早期研究只关注准确性，并没有解释延迟发生的原因。这项研究通过将达卡Hazrat Shahjalal国际机场（HSIA）的预测模型与可解释的人工智能（XAI）相结合，填补了这一空白。我们使用2022年以来的航班和天气数据，通过清理数据、创建新特征和组合信息，创建了一个完整的数据集。我们测试了几种模型，包括KNN、支持向量机、决策树、随机森林、AdaBoost、XGBoost和CatBoost。结果表明，集成模型表现最好，CatBoost和XGBoost的准确率达到95%。为了使这些模型更容易理解，我们使用了LIME方法，结果表明天气和调度是影响延误的主要因素。这项研究独特地应用了可解释的机器学习来预测发展中国家的航班延误，特别是在孟加拉国的Hazrat Shahjalal国际机场。以前的研究大多集中在英国、美国、沙特阿拉伯或中国等国家。通过提供准确的预测和明确的解释，结果显示航空公司和机场当局如何改进调度，更好地利用资源，并达到国际延误标准。这有助于提高乘客满意度和增强机场的应变能力。

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引用次数: 0

Environmental awareness and infrastructure – A path to sustainable transport in Central and Eastern European Countries 环境意识和基础设施——中欧和东欧国家通往可持续交通的道路

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-12-04 DOI: 10.1016/j.cstp.2025.101675

Agata Kliber , Blanka Łęt , Pavel Řezáč , Barbara Będowska-Sójka , Jindřich Frič

Reducing the use of combustion cars is one of the crucial aspects of the current environmental policy of the European Union. This article analyses how environmental awareness and the perceived quality of public transport and cycling infrastructure influence daily mobility mode choice in the Visegrad Group economies. We collected the data through surveys run in these countries from December 2023 to January 2024. We estimated a multilogit model with latent attitudinal variables. We demonstrate that ecological awareness is one of the key factors influencing consumers’ decisions about choosing transport modes other than a car. However, commuting remains predominantly car-based in all countries studied. Our results suggest that, when planning infrastructure that will encourage residents to use sustainable transport, decision-makers should prioritise creating good public transport connections with shopping centres, while cycling infrastructure should be linked to workplace and school locations.

减少内燃机汽车的使用是欧盟当前环境政策的关键方面之一。本文分析了环境意识、公共交通和自行车基础设施的感知质量如何影响维谢格拉德集团经济体的日常出行方式选择。我们通过从2023年12月到2024年1月在这些国家进行的调查收集数据。我们估计了一个具有潜在态度变量的多重logit模型。研究表明，生态意识是影响消费者选择汽车以外交通方式的关键因素之一。然而，在所研究的所有国家中，通勤仍然以汽车为主。我们的研究结果表明，在规划鼓励居民使用可持续交通的基础设施时，决策者应优先考虑与购物中心建立良好的公共交通连接，而自行车基础设施应与工作场所和学校地点联系起来。

引用次数: 0

What drives workers to be heavily reliant on cars in commuting to workplaces? Investigations of commute behaviour in Melbourne 是什么驱使工人们严重依赖汽车上下班？墨尔本通勤行为调查

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-12-02 DOI: 10.1016/j.cstp.2025.101679

Fadhlullah Apriandy , Sugiarto Sugiarto , Yusria Darma , Irsan Bahrumy

As the largest proportion of weekdays trips in Melbourne, Australia, work commutes, even in short distance, are predominantly attributed to cars. This study aims to investigate as to why Melbourne residents are heavily reliant on cars in commuting to workplaces. To better understand variations of car dependencies across different parts of the city and commute distances, this study divides Melbourne into three regions namely inner, middle, and outer Melbourne and set boundaries of commute distances to walkable (≤ 2.5 km), bikeable (2.5 to 15 km), and long (≥ 15 km). Multinomial Logistic models were utilized to explore the Victorian Integrated Survey of Travel and Activity (VISTA) data that contains travel, socio-demographic, and built environment factors. Variables were found to exhibit varying impacts on work commute behaviours across regions and distances. Overall, possessing a car license is associated with car uses across all distances. In walkable distance commutes, a km increase in commute distance significantly increases the likelihood of using cars. Inner Melbourne residents exhibit the tendency of using car in bikeable and long-distance commutes with the increasing number of cars owned. The findings of this study could help stakeholders in developing interventions to mitigate car dependency in work commutes.

作为澳大利亚墨尔本工作日出行比例最大的城市，即使距离很近，上班通勤也以汽车为主。这项研究的目的是调查为什么墨尔本居民严重依赖汽车通勤到工作场所。为了更好地了解城市不同地区和通勤距离的汽车依赖变化，本研究将墨尔本分为内、中、外三个区域，并将通勤距离划分为步行（≤2.5公里）、骑自行车（2.5至15公里）和长途（≥15公里）。使用多项Logistic模型来探索维多利亚旅行和活动综合调查（VISTA）数据，其中包含旅行，社会人口统计和建筑环境因素。研究发现，不同地区和距离的变量对工作通勤行为的影响是不同的。总的来说，拥有汽车执照与所有距离的汽车使用有关。在步行距离通勤中，通勤距离每增加一公里，使用汽车的可能性就会显著增加。随着汽车拥有量的增加，内墨尔本居民在骑自行车和长途通勤中表现出使用汽车的趋势。这项研究的发现可以帮助利益相关者制定干预措施，以减轻工作通勤中的汽车依赖。

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引用次数: 0

Machine learning for predicting the public adoption of partial and fully automated vehicle in Indonesia 机器学习预测印尼公众对部分和完全自动驾驶汽车的采用

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-12-02 DOI: 10.1016/j.cstp.2025.101678

Achmad Pratama Rifai , Fitri Trapsilawati , Erlangga Satrio Agung , Ari Widyanti , Roger Woodman , Auditya Purwandini Sutarto , Nachnul Ansori

This study investigates the public adoption of Partially Autonomous Vehicles (PAV) and Fully Autonomous Vehicles (FAV) in Indonesia, utilizing machine learning algorithms to predict willingness to use (WTU) and willingness to buy (WTB). Data were collected through an online survey of 1,251 Indonesian respondents, considering 38 socio-demographic, psychological, and mobility factors. Using Artificial Neural Networks (ANN) and Support Vector Machines (SVM), predictive models were developed and evaluated. The results highlight that ANN models exhibit higher accuracy for FAV predictions (MAPE = 11.246 %), while SVM models demonstrate efficiency with shorter training times. The results show that trust, perceived safety, and social influence strongly shape adoption intentions, with behavioural complexity increasing from PAV to FAV. These findings provide evidence-based guidance for policymakers and industry stakeholders preparing for autonomous mobility in Indonesia. The study acknowledges limitations related to online sampling and the absence of longitudinal behavioral data.

本研究调查了印度尼西亚公众对部分自动驾驶汽车（PAV）和完全自动驾驶汽车（FAV）的采用情况，利用机器学习算法预测使用意愿（WTU）和购买意愿（WTB）。数据是通过对1251名印尼受访者的在线调查收集的，考虑了38个社会人口、心理和流动性因素。利用人工神经网络（ANN）和支持向量机（SVM）建立预测模型并进行评估。结果表明，人工神经网络模型对FAV的预测具有更高的准确性（MAPE = 11.246%），而支持向量机模型在更短的训练时间内表现出更高的效率。结果表明，信任、感知安全性和社会影响强烈地影响着收养意愿，行为复杂性从PAV到FAV逐渐增加。这些发现为印尼的政策制定者和行业利益相关者准备自主出行提供了基于证据的指导。该研究承认在线抽样和缺乏纵向行为数据的局限性。

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引用次数: 0

Inference of parking search and location choice behavior using trip trajectories and Bayesian statistics 基于出行轨迹和贝叶斯统计的停车搜索和位置选择行为推断

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-11-29 DOI: 10.1016/j.cstp.2025.101671

Prakash Ranjan , Fatemeh Fakhrmoosavi , Krishna M. Gurumurthy , Abdelrahman Ismael , Nazmul A. Khan

Effectively designed parking solutions play a crucial role in mitigating urban challenges such as traffic congestion, excessive fuel consumption, and reduced safety. This study integrates GPS data with traveler survey data to model parking choice behavior, including preferences for parking type and choice for specific garage. Given the hierarchical nature of the choices, a nested logit model was estimated within a Bayesian framework using the Metropolis-Hastings algorithm. This approach is particularly efficient for high-dimensional models due to its fast convergence and straightforward implementation. The model was subsequently implemented within an agent-based transportation system simulation tool, POLARIS, to analyze the variations in drivers’ parking choice under diverse parking fee and capacity restriction scenarios. Analysis of the simulated scenarios for the Chicago network representing 8.5 million population revealed that while parking fee adjustments significantly impact travelers’ parking choices, fee variations during peak periods have minimal effect. For instance, a 50% rise in garage fees decreased the number of garage travelers by approximately 20%. However, raising garage fees by the same amount (50%) in the city during peak traffic periods led to a marginal drop of 7% in garage demand. Parking agencies generally set fees on the higher side to increase profit margins. However, parking policies should be designed to balance both travelers’ and transportation agencies’ interests in the long run. In addition, this study shows that allocating a portion of parking spaces to reserved parking or specific vehicle types, for a better curb space and parking management, significantly influences travelers’ decision-making in the parking choice selection.

有效设计的停车解决方案在缓解交通拥堵、过度油耗和安全性降低等城市挑战方面发挥着至关重要的作用。本研究将GPS数据与旅行者调查数据相结合，对停车选择行为进行建模，包括对停车类型的偏好和对特定车库的选择。考虑到选择的层次性，使用Metropolis-Hastings算法在Bayesian框架内估计嵌套logit模型。由于其快速收敛和简单的实现，该方法对高维模型特别有效。该模型随后在基于代理的交通系统仿真工具POLARIS中实施，以分析不同停车收费和容量限制情景下驾驶员停车选择的变化。对代表850万人口的芝加哥网络的模拟情景分析显示，停车费用的调整对旅客的停车选择有显著影响，而高峰时段的费用变化影响最小。例如，车库费上涨50%，车库旅行者的数量减少了大约20%。然而，在交通高峰期将车库费提高50%，导致车库需求小幅下降7%。停车代理机构通常将收费定得较高，以增加利润率。然而，从长远来看，停车政策的设计应该平衡旅客和运输机构的利益。此外，本研究还表明，为了更好地控制路边空间和管理停车，将一部分停车位分配给预留停车位或特定车型，显著影响出行者的停车选择决策。

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引用次数: 0

Understanding employee and managerial acceptance of flexible working arrangements as a transport policy in the Philippines: A sectoral comparative analysis 了解员工和管理接受灵活的工作安排作为运输政策在菲律宾：部门比较分析

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-11-29 DOI: 10.1016/j.cstp.2025.101677

Jayrill T. Condeza , Hitomi Sato , Tomio Miwa

Using behavioral theories, such as the modified unified theory of acceptance and use of technology (UTAUT), we extended the analysis of non-infrastructure travel demand management (TDM) strategies, such as flexible work arrangements (FWA), in managing the urban mobility of employees and managers beyond the constraints of classical transport policy evaluation. This study uses the classical UTAUT constructs – performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), and personal attitude (PA) – and additional psychological constructs, subjective wellbeing (SWB), work-life balance (WLB), and employee satisfaction (ES), to capture the underlying nuances, motivations, and concerns regarding the behavioral intention (BI) of adopting FWA. We further conducted a multigroup analysis to investigate whether the acceptance behavior of key stakeholders in the government and private sectors differ significantly. The findings suggest that the significant influence and perceived benefits of PA, PE, and WLB among employees and managers reveal the potential impacts of FWA in decongesting metropolitan urban spaces, especially during peak hours, reinforcing the idea of employing non-infrastructure TDM policies to help alleviate the worsening traffic conditions in major thoroughfares of the Philippines, as stipulated in the National Transport Policy. Additionally, these results identify the key areas of concern for both employees and managers affecting FWA adoption, enabling policymakers and organizational leaders to formulate more equitable sector-specific policies and guidelines to help achieve and sustain the identified potential benefits of time and cost savings, improved work performance, better quality of life, and positive environmental outcomes.

利用行为理论，如改进的技术接受和使用统一理论（UTAUT），我们扩展了非基础设施旅行需求管理（TDM）策略的分析，如灵活工作安排（FWA），在管理员工和管理人员的城市流动性方面超越了经典交通政策评估的约束。本研究使用经典的UTAUT构构——绩效期望（PE）、努力期望（EE）、社会影响（SI）、促进条件（FC）和个人态度（PA），以及额外的心理构构——主观幸福感（SWB）、工作与生活平衡（WLB）和员工满意度（ES），来捕捉采用FWA的行为意向（BI）的潜在细微差别、动机和关注点。我们进一步进行了多群体分析，以调查政府和私营部门关键利益相关者的接受行为是否存在显著差异。研究结果表明，PA、PE和WLB在员工和管理人员中的显著影响和感知效益揭示了FWA在缓解大都市城市空间拥堵方面的潜在影响，特别是在高峰时段，强化了采用非基础设施TDM政策来帮助缓解菲律宾主要道路交通状况恶化的想法，正如国家交通政策所规定的那样。此外，这些结果确定了影响FWA采用的员工和管理人员关注的关键领域，使政策制定者和组织领导人能够制定更公平的针对特定行业的政策和指导方针，以帮助实现和维持已确定的节省时间和成本、提高工作绩效、提高生活质量和积极的环境结果的潜在利益。

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引用次数: 0

Strategic framework to improve the value chain of end-of-life vehicles in Malaysia 改善马来西亚报废车辆价值链的战略框架

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-11-27 DOI: 10.1016/j.cstp.2025.101676

Jia Yuik Chong , Muhamad Zameri Mat Saman , Norhayati Zakuan , Nor Hasrul Akhmal Ngadiman

End-of-life vehicles (ELV) management is crucial for sustainable development in a circular economy and waste minimization for the conservation of natural resources. However, there is still improper connection between the National Automotive Policy (NAP) 2020 implementation and the ELV strategies development in the supply chain of the Malaysian automotive industry. ELV recycling and remanufacturing companies face difficulties adopting appropriate ELV implementation strategies for used parts recovery in ELV. Therefore, this study aims to develop a strategic framework to improve the value chain of ELV in Malaysia. The study adopted qualitative interview approach with a total of nine respondents from six ELV recycling companies as multiple case studies. The three directions identified are optimization of ELV used parts/cores supply and demand, recovery of ELV used parts/cores, and improvement of ELV used parts/cores quality. Nine sub-strategies were proposed to address the corresponding critical enablers (strengths and opportunities) and inhibitors (weaknesses and threats) to improve the ELV value chain. Based on their contextual relevance, these sub-strategies were categorized into two main strategies: 1) value chain development, and 2) human capital and technological development. Lastly, a strategic framework which consists of three key focus directions and two main strategies was developed. The proposed strategic framework serves as a pathway for implementing future ELV policy in Malaysia, in line with NAP 2020. The ELV-related companies, government agencies and industry stakeholders especially in developing countries can adopt this strategic framework to formulate appropriate directions and strategies to optimize their ELV value chain for sustainable development.

报废车辆（ELV）管理对于循环经济的可持续发展和减少废物以保护自然资源至关重要。然而，国家汽车政策（NAP） 2020的实施与马来西亚汽车行业供应链中的ELV战略发展之间仍然存在不适当的联系。ELV回收和再制造企业在采用合适的ELV实施策略进行ELV废旧零部件回收方面面临困难。因此，本研究旨在制定一个战略框架，以改善马来西亚的电动汽车价值链。本研究采用质性访谈法，选取6家ELV回收公司共9名受访者作为多案例研究。确定了三个方向：电气化车废旧件/芯供需优化、电气化车废旧件/芯回收、电气化车废旧件/芯质量提升。提出了9个子战略，以解决相应的关键推动因素（优势和机会）和抑制因素（弱点和威胁），以改善ELV价值链。根据其上下文相关性，将这些子战略分为两个主要战略：1)价值链发展战略和2)人力资本和技术发展战略。最后，制定了由三个重点方向和两个主要战略组成的战略框架。拟议的战略框架是在马来西亚实施未来低成本汽车政策的途径，符合NAP 2020。特别是发展中国家的电动汽车相关企业、政府机构和行业利益相关者可以采用这一战略框架，制定适当的方向和战略，优化其电动汽车价值链，实现可持续发展。

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引用次数: 0

Urban transport planning in Saudi Arabia: A systematic review of challenges and smart mobility pathways 沙特阿拉伯的城市交通规划：挑战和智能移动路径的系统回顾

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-11-26 DOI: 10.1016/j.cstp.2025.101674

Md. Ebrahim Shaik , Alamein Mohammed Hassab Algabo Hassan , Sayed Abdul Jabar Rahmani , Hassan Musaed Al-Ahmadi

The growing demand for urban mobility in Saudi Arabia presents significant challenges to the sustainability and effectiveness of its transportation systems. This study provides a systematic review of urban transport planning in Saudi cities, focusing on public transport development, smart mobility strategies, and associated implementation barriers. This study adopts the PRISMA methodology to ensure transparency and reproducibility in article selection and synthesis. Additionally, bibliometric techniques were applied to identify thematic research clusters. The findings highlight the dominance of private vehicle use, the underdevelopment of public transport systems, and fragmented governance structures as major challenges. In response, the study proposes a conceptual framework for classifying urban transport barriers and offers necessary insights to align local initiatives with future visions. The review contributes practical insights for policymakers and urban planners working toward integrated, sustainable, and inclusive mobility solutions in Saudi Arabia.

沙特阿拉伯日益增长的城市交通需求对其交通系统的可持续性和有效性提出了重大挑战。本研究对沙特城市的城市交通规划进行了系统回顾，重点关注公共交通发展、智能交通战略和相关的实施障碍。本研究采用PRISMA方法，以确保文章选择和合成的透明度和可重复性。此外，应用文献计量学技术来确定专题研究集群。调查结果强调，私人车辆使用占主导地位、公共交通系统不发达以及治理结构分散是主要挑战。作为回应，该研究提出了一个分类城市交通障碍的概念框架，并提供了必要的见解，使地方举措与未来愿景保持一致。该综述为政策制定者和城市规划者在沙特阿拉伯制定综合、可持续和包容的交通解决方案提供了实际见解。

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引用次数: 0

Equity analysis of urban transportation network resilience with urban air mobility integration 考虑城市空中交通一体化的城市交通网络弹性公平性分析

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2025-11-26 DOI: 10.1016/j.cstp.2025.101673

Zhiao Ma , Zhuowei Wang , Yiyang Peng , Yingying Xu , Anthony Chen , Xin Yang , Jianjun Wu

Faced with chronic traffic congestion and spatial inequities, global megacities urgently need urban air mobility (UAM) integration to enhance transportation resilience and promote equitable mobility. This study constructs a constrained clustering model to identify vertiport locations, considering no-fly zones and integrating passenger flow demand and point of interest (POI) distribution. By constructing a two-layer transport network and employing percolation theory, we systematically evaluate how vertiport deployment strategies impact regional-level resilience and equity. The findings of the Beijing case reveal the relationship between deployment scale and resilience equity. Moderate deployment helps to improve and compensate for regional resilience differences, balance efficiency and fairness, but large-scale deployment exacerbates inequality. This research underscores the importance of strategic and non-uniform vertiport siting to mitigate urban transport disparities, providing theoretical insights and policy recommendations for equitable UAM development.

面对长期的交通拥堵和空间不平等，全球特大城市迫切需要城市空中交通（UAM）一体化，以增强交通弹性，促进交通公平。本文在考虑禁飞区的基础上，结合客流需求和兴趣点分布，构建了一个约束聚类模型来确定垂直机场的位置。通过构建两层运输网络并运用渗透理论，我们系统地评估了垂直机场部署策略如何影响区域层面的弹性和公平性。北京案例的发现揭示了部署规模与弹性公平之间的关系。适度部署有助于改善和弥补区域弹性差异，平衡效率和公平，但大规模部署会加剧不平等。本研究强调了战略性和非统一垂直机场选址对于缓解城市交通差异的重要性，为公平的垂直机场发展提供了理论见解和政策建议。

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引用次数: 0