Case Studies on Transport Policy最新文献

Anticipating the consequences of zero-occupant vehicles (ZOV): a qualitative study of urban mobility impacts in Toronto 预测零乘员车辆（ZOV）的后果：多伦多城市交通影响的定性研究

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2026-01-29 DOI: 10.1016/j.cstp.2026.101735

Lisa L. Losada-Rojas , Eric J. Miller

The impact of Autonomous Vehicles (AVs) on our everyday lives depends on their usage and operation, as they can yield either favorable or unfavorable outcomes. AVs with self-driving capabilities can generate trips by zero-occupancy vehicles (ZOVs), i.e., AVs that travel without passengers. Unlike occupied AVs that replace human-driven trips, ZOVs generate additional empty vehicle circulation as they reposition between trips or seek parking, raising distinct concerns for traffic management, environmental sustainability, and infrastructure planning. While prior research has focused on quantitative modeling of ZOV impacts, policymakers and stakeholders’ perspectives on regulating this emerging technology remain underexplored. This study addresses this gap through qualitative analysis of focus groups and interviews with 45 stakeholders in Toronto, Canada, including planners, engineers, and policymakers. Toronto provides a relevant case study as a major North American city actively planning for AV deployment, with municipal authority over transportation policy that enables regulatory innovation. Through thematic analysis, we identify key policy concerns such as congestion management, environmental sustainability, infrastructure adaptation, and the economic implications of AV adoption. Stakeholders emphasized the need for regulatory interventions to limit unnecessary ZOV trips. Specific recommendations include establishing dedicated lanes and designated testing areas for safe ZOV deployment, creating comprehensive mobility pricing frameworks, and leveraging data from connected vehicles and infrastructure for real-time traffic management and emergency response prioritization. Standardization and cross-sector collaboration between government, industry, and academia were seen as critical to ensuring an effective transition. Our findings provide evidence-based guidance for policymakers navigating the regulatory challenges of ZOV deployment and highlight the need for adaptive, collaborative governance approaches in the context of rapidly evolving autonomous vehicle technology.

自动驾驶汽车（av）对我们日常生活的影响取决于它们的使用和操作，因为它们可以产生有利或不利的结果。具有自动驾驶功能的自动驾驶汽车可以通过零占用车辆（zov）产生行程，即没有乘客的自动驾驶汽车。与无人驾驶汽车取代人类驾驶的出行方式不同，zov会在行程之间重新定位或寻找停车位，从而产生额外的空车循环，这引起了人们对交通管理、环境可持续性和基础设施规划的明显关注。虽然之前的研究主要集中在ZOV影响的定量建模上，但政策制定者和利益相关者对监管这一新兴技术的看法仍未得到充分探讨。本研究通过对焦点小组的定性分析和对加拿大多伦多45名利益相关者的访谈来解决这一差距，其中包括规划师、工程师和政策制定者。作为积极规划自动驾驶汽车部署的北美主要城市，多伦多提供了一个相关的案例研究，市政当局制定了交通政策，从而实现了监管创新。通过专题分析，我们确定了关键的政策问题，如拥堵管理、环境可持续性、基础设施适应和自动驾驶采用的经济影响。利益相关者强调需要进行监管干预，以限制不必要的ZOV行程。具体建议包括为安全部署ZOV建立专用车道和指定测试区域，创建全面的移动定价框架，以及利用互联车辆和基础设施的数据进行实时交通管理和应急响应优先级排序。政府、工业界和学术界之间的标准化和跨部门合作被视为确保有效过渡的关键。我们的研究结果为政策制定者提供了基于证据的指导，以应对ZOV部署的监管挑战，并强调了在快速发展的自动驾驶汽车技术背景下，需要采用自适应、协作的治理方法。

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引用次数: 0

A hybrid SEM–ANN framework for predicting crash involvement and prioritizing safety strategies among LCV drivers in India 混合SEM-ANN框架预测碰撞参与和优先安全策略在印度的LCV司机

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2026-01-29 DOI: 10.1016/j.cstp.2026.101728

Karamsetty Pavan Kumar, Balamurugan Shandhana Rashmi, Sankaran Marisamynathan

Road traffic crashes (RTCs) are major public concerns causing societal and economic burden worldwide. According to empirical data, most crashes are caused by drivers engaging in risky driving behaviour. However, in developing nations like India, limited research exists on crash involvement of professional drivers, including light commercial vehicle drivers (LCVs). Therefore, the aim of the present research to study the determinants of crash involvement and develop a prediction model for LCV drivers. Further, the study also recommends suitable strategies for improving the safety of LCV drivers. To accomplish this, face-to-face interviews with LCV drivers were carried out using a questionnaire form in Nellore city, Andhra Pradesh, India. The questionnaire consisted of items related to personality traits, work safety climate, driver safety attitude, risky driving behaviour and crash involvement of LCV drivers. Data collection yielded 605 valid samples for further study. The exploratory factor analysis obtained a four-factor structure (sensation seeking, normlessness, anxiety, and anger) for the personality traits items, which was subsequently validated by confirmatory factor analysis. To analyze the complex relationships among several latent constructs and develop a prediction model for crash involvement, a hybrid Structural Equation Modeling and Artificial Neural Network (SEM-ANN) methods were adopted in this study. The ranking results from the ANN model demonstrated that risky driving behavior as the utmost influential predictor of crash involvement. Further, the analysis of safety strategies using the ANN model identified GPS-ANPR integrated enforcement of traffic rules as the most effective interventions, with normalized importance scores of 100%, followed by regular health checkup of drivers (94.19%), and installing of telematic systems (82.90%). The outcomes indicate the importance of enforcement-driven and technology-based strategies for improving LCV drivers’ safety. The outcomes of this study offer valuable insights for Indian trucking companies and road safety authorities to enhance the safety of LCV drivers.

道路交通碰撞是世界范围内造成社会和经济负担的主要公共问题。根据经验数据，大多数撞车事故是由驾驶员从事危险驾驶行为造成的。然而，在像印度这样的发展中国家，对专业驾驶员（包括轻型商用车驾驶员）的碰撞参与研究有限。因此，本研究的目的是研究碰撞卷入的决定因素，并建立一个LCV驾驶员的预测模型。此外，该研究还建议了适当的策略来提高LCV驾驶员的安全性。为此，在印度安得拉邦内洛尔市使用问卷形式对轻型货车司机进行了面对面访谈。问卷内容包括人格特征、工作安全氛围、驾驶员安全态度、危险驾驶行为和轻型车驾驶员碰撞卷入等。数据收集得到605个有效样本供进一步研究。探索性因子分析获得了人格特质项目的四因子结构（感觉寻求、不规范、焦虑和愤怒），并通过验证性因子分析对其进行验证。为了分析多个潜在构式之间的复杂关系，建立碰撞卷入预测模型，本研究采用结构方程建模和人工神经网络（SEM-ANN）相结合的方法。人工神经网络模型的排名结果表明，危险驾驶行为是最具影响力的预测因素。此外，利用人工神经网络模型对安全策略进行分析，发现GPS-ANPR综合执行交通规则是最有效的干预措施，标准化重要性得分为100%，其次是驾驶员定期健康检查（94.19%）和安装远程信息处理系统（82.90%）。结果表明，执法驱动和基于技术的策略对于提高LCV驾驶员的安全至关重要。这项研究的结果为印度卡车运输公司和道路安全当局提供了有价值的见解，以提高LCV驾驶员的安全性。

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引用次数: 0

Understanding multi-stage adaptation behavior under climate extremes: evidence from Bangladesh 理解极端气候下的多阶段适应行为：来自孟加拉国的证据

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2026-01-28 DOI: 10.1016/j.cstp.2026.101731

Xin-Yu Zuo , Qing-Chang Lu , Peng-Cheng Xu , Biao Xu , Ying Jiang , Junyi Zhang

Adaptation behavior usually involves a dynamic learning and decision-making process over an extended multi-stage period. However, such a perspective has remained unexplored in existing studies. To address this gap, this study investigates multi-stage adaptive and intercity travel behavior in response to climate change. A life-oriented revealed preference-stated preference (RP-SP) survey was implemented across 1 4 regions of Bangladesh, one of the most climate-affected countries globally. A dynamic paired combinatorial logit model is developed to examine state dependence effects across three stages of disaster: before-disaster preparedness, during-disaster response, and future adaptation. The results indicate that adaptive behaviors evolve dynamically across different stages and are significantly influenced by prior experiences. Future adaptations exhibit state-dependent effects rooted in both before-disaster and during-disaster stages. Structural damage to housing increases the likelihood of changes in intercity travel destinations, while those whose quality of life is severely affected are more inclined to cancel their travel plans. Households with more female members tend to engage more in preventive preparedness behaviors before disasters, whereas male members play a dominant role in implementing protective measures such as house elevation during disasters.

适应行为通常包括一个动态的学习和决策过程，这个过程持续了很长一段时间。然而，这一观点在现有的研究中仍未得到探索。为了解决这一差距，本研究调查了气候变化下的多阶段适应和城际旅行行为。在全球受气候影响最严重的国家之一孟加拉国的14个地区实施了一项以生活为导向的揭示偏好-陈述偏好（RP-SP）调查。本文建立了一个动态配对组合逻辑模型，用于检验灾难三个阶段的状态依赖效应：灾前准备、灾中响应和未来适应。结果表明，适应行为在不同阶段是动态演化的，且受前期经验的显著影响。未来的适应表现出植根于灾前和灾中阶段的状态依赖效应。住房的结构性破坏增加了城际旅行目的地改变的可能性，而那些生活质量受到严重影响的人更倾向于取消旅行计划。女性成员较多的家庭往往在灾害发生前更多地参与预防准备行为，而男性成员在灾害期间实施房屋抬高等保护措施方面发挥主导作用。

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引用次数: 0

Simulation-based evaluation of low emission zone-rail impacts on emissions and logistics efficiency: Case study of Rotterdam, The Netherlands 基于模拟的低排放区铁路对排放和物流效率影响评估——以荷兰鹿特丹为例

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2026-01-21 DOI: 10.1016/j.cstp.2026.101720

Dominic Kwakye Ampong, Libor Švadlenka, Molková Tatiana, Libor Bauer

Aligned with sustainable development goals (SDGs) and European Union policy goals, including the Green Deal, this study examines the integration of low-emission zones (LEZs) with rail logistics to enhance sustainable urban freight transport. While existing research focuses on standalone LEZs policies for passenger vehicles, the role of rail in freight decarbonization has been underexplored. The study develops a dynamic simulation model to compare the policies of only LEZs, LEZs + Rail, and LEZs + Multimodal, to assess their impact on emissions and logistics efficiency, focusing on achieving the SDGs. A case study from the European logistics sector was conducted in Rotterdam, The Netherlands. To ensure robustness of the simulation, the freight data and emission factors for validating the model were adopted from the Covenant-Zero-Emission-City-Logistics-Rotterdam and STREAM report for freight transport (CE Delft). This study is structured into four phases. The first phase involves data collection, system characterization, input of the simulation model, and assumption validation. The second phase is emission estimation using the Groot-Rijnmond model. The third phase includes the formulation of the dynamic simulation model. Finally, the fourth phase involves the development of scenarios and the testing of policies. The results highlight the potential of the LEZs–rail synergy to enhance the efficiency of the last mile logistics and significantly reduce transportation-related emissions in dense urban settings. The findings indicate that dynamic access pricing and multimodal logistics hubs facilitate a 55 percent shift toward rail freight, improving economic efficiency and resilience to supply chains. Furthermore, while a fixed congestion charge reduces freight emissions approximately 20 percent by 2030, a fully optimized dynamic pricing + rail strategy achieves a 50–55 percent reduction. Sensitivity analysis confirms the robustness of the results, demonstrating the applicability of the model to complex and dynamic decision-making contexts. This study offers theoretical contributions and practical insights for decision makers looking to improve the sustainability of urban logistics while ensuring economic viability and operational efficiency.

根据可持续发展目标（sdg）和欧盟政策目标（包括绿色协议），本研究探讨了低排放区（LEZs）与铁路物流的整合，以加强可持续的城市货运。虽然现有的研究主要集中在客运车辆的独立低碳区政策上，但铁路在货运脱碳中的作用尚未得到充分探讨。该研究开发了一个动态仿真模型，以比较仅限lez、lez + Rail和lez + Multimodal的政策，以评估其对排放和物流效率的影响，重点是实现可持续发展目标。在荷兰鹿特丹进行了欧洲物流部门的案例研究。为了确保模拟的鲁棒性，用于验证模型的货运数据和排放因子采用了公约-零排放城市-物流-鹿特丹和货运STREAM报告（CE Delft）。本研究分为四个阶段。第一阶段包括数据收集、系统表征、仿真模型输入和假设验证。第二阶段是使用Groot-Rijnmond模型进行排放估计。第三阶段包括动态仿真模型的建立。最后，第四个阶段涉及场景的开发和政策的测试。研究结果强调了低污染区与铁路协同作用的潜力，可以提高最后一英里物流的效率，并显著减少人口密集城市环境中与运输相关的排放。研究结果表明，动态准入定价和多式联运物流中心促进了55%的铁路货运转移，提高了经济效率和供应链弹性。此外，到2030年，固定的拥堵费可以减少约20%的货运排放，而完全优化的动态定价+铁路战略可以减少50 - 55%的排放。敏感性分析证实了结果的稳健性，表明该模型适用于复杂和动态的决策环境。本研究为决策者在确保经济可行性和运营效率的同时提高城市物流的可持续性提供了理论贡献和实践见解。

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引用次数: 0

Forecasting electric air taxi demand and modal shift for airport travel: a case study of northern Utah 预测机场出行的电动空中出租车需求和模式转变：以犹他州北部为例

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2026-01-21 DOI: 10.1016/j.cstp.2026.101716

Atul Subedi, Patrick A. Singleton

This study addressed key knowledge gaps by forecasting electric air taxi (EAT) demand for airport access—one of the earliest and most promising use cases for EAT deployment. Unlike prior EAT studies focused on short urban trips, this research analyzed a long-distance corridor in northern Utah, United States, where the substantial travel time savings make it a highly feasible setting for early adoption. Methods combined a revealed preference–stated preference (RP–SP) mixed logit model with observed origin–destination travel data. The first objective assessed mode shifts following the introduction of EAT service for airport trips. Results show EAT could divert approximately one-third of trips from private vehicles and ride-hailing, reducing corridor traffic by over 160 vehicles daily. This shift could reduce airport parking demand and tailpipe emissions, improving air quality. Forecasts also predict a modest decline in public transportation ridership from approximately 6% to 3%, potentially undermining bus service revenue and disproportionately impacting lower-income travelers. The second objective conducted sensitivity analyses to evaluate the robustness of EAT demand to various factors. Findings revealed that in-vehicle travel time, travel cost, service frequency, autonomy, and the number of parking days significantly influenced mode shifts. EAT market share was projected to increase from 17% at a higher EAT travel cost of $4.50/mile (near-term) to 63% at a lower EAT travel cost of $0.50/mile (long-term). Vertiport expansion in the study area showed diminishing returns beyond one site, suggesting locations for priority deployment. These findings support evidence-based planning and equitable implementation of EAT services.

本研究通过预测机场通道对电动空中出租车（EAT）的需求，解决了关键的知识缺口，这是EAT部署最早和最有前途的用例之一。不同于以往的EAT研究侧重于短途城市旅行，本研究分析了美国犹他州北部的长途走廊，在那里节省了大量的旅行时间，使其成为早期采用的高度可行的环境。方法将显示偏好-陈述偏好（RP-SP）混合logit模型与观察到的出发地旅行数据相结合。第一个目标是评估在引入机场自助出行服务后的模式转变。研究结果显示，EAT可以将大约三分之一的出行从私家车和网约车中转移出来，每天减少160多辆走廊交通。这种转变可以减少机场停车需求和尾气排放，改善空气质量。预测还预测，公共交通客流量将从大约6%小幅下降至3%，这可能会削弱公交服务的收入，并对低收入旅客造成不成比例的影响。第二个目标进行敏感性分析，以评估EAT需求对各种因素的稳健性。结果显示，乘车时间、出行成本、服务频率、自主性和停车天数显著影响出行方式的转变。预计EAT的市场份额将从近期4.50美元/英里的高EAT旅行成本（17%）增加到长期0.50美元/英里的低EAT旅行成本（63%）。在研究区域内的垂直机场扩展显示出超出一个站点的收益递减，建议优先部署的位置。这些发现支持循证规划和公平实施EAT服务。

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引用次数: 0

Vehicle routing with Backhauls in retail: a case study 零售中带回运的车辆路线：一个案例研究

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2026-01-21 DOI: 10.1016/j.cstp.2026.101715

Marcelo Koiti Fugihara, Marcel Heimar Ribeiro Utyama, Mauro Sampaio

This study examines the impact of integrating backhaul operations into outbound distribution routes in the Brazilian retail sector, utilizing real operational data from a large home improvement retailer. Building on the Vehicle Routing Problem with Backhauls (VRPB), the research incorporates operational constraints highly relevant to transport policy and logistics management, such as last-in/first-out loading, heterogeneous vehicle capacities, warehouse handling times, and driver working-time regulations. A directed network model was developed and evaluated in Coupa Supply Chain Guru® X, enabling the simulation and comparison of alternative routing strategies. Results show that coordinated outbound–inbound planning can reduce transportation costs by nearly 30%, increase vehicle utilization, and decrease CO₂ emissions by approximately 10 tons annually. The case provides evidence of how backhaul-based routing can enhance efficiency and environmental performance in emerging-economy retail networks. The findings provide practical guidance for companies and policymakers seeking to reduce empty-haul movements, promote sustainable freight transport, and support circular economy initiatives within regional distribution systems.

本研究利用一家大型家装零售商的真实运营数据，考察了将回程业务整合到巴西零售业的出站分销路线中的影响。该研究以带回运的车辆路线问题（VRPB）为基础，结合了与运输政策和物流管理高度相关的操作约束，如后进/先出装载、异构车辆容量、仓库处理时间和驾驶员工作时间规定。在Coupa Supply Chain Guru®X中开发并评估了一个定向网络模型，实现了可选路由策略的仿真和比较。结果表明，协同出入地规划可使运输成本降低近30%，提高车辆利用率，每年减少二氧化碳排放约10吨。该案例证明了基于回程的路线如何能够提高新兴经济体零售网络的效率和环境绩效。研究结果为寻求减少空载运输、促进可持续货运和支持区域配送系统内循环经济举措的公司和政策制定者提供了实用指导。

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引用次数: 0

Autonomous shuttles in the public eye: mediators on the path to successful expansion 公众眼中的自动驾驶航天飞机：成功扩张道路上的调解人

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2026-01-19 DOI: 10.1016/j.cstp.2026.101719

Panick Kalambay , Norris Novat , Boniphace Kutela , Abimbola Ogungbire , Angela Kitali , Emmanuel Kidando

This study explored public opinions on the expansion and safety of autonomous shuttles using data from the Connected Autonomous Shuttle Supporting Innovation (CASSI) pilot program in Cary and Charlotte, North Carolina. The objective is to understand the factors influencing public support or opposition to autonomous shuttle expansion, investigate perceptions of safety, and uncover reasons for reluctance to re-ride. For this purpose, the study employed ranked cross-correlation analysis, association rule mining, mediation analysis, and thematic analysis. Key mediators, such as post-ride safety perception and the intention to re-ride, were identified, and the findings reveal that they significantly influence public support for shuttle expansion. In addition, the importance of positive initial experience, timely service, and enhanced operational performance in fostering public acceptance was also highlighted. Overall, the findings underscore the need to address safety concerns, ensure accessibility, and improve shuttle operations to promote large-scale adoption. This study provides valuable insights into the intersection of public opinion on safety and autonomous shuttle operation, guiding policymakers and service providers to better integrate these vehicles into urban transportation systems.

本研究利用北卡罗莱纳州卡里和夏洛特市的互联自动驾驶航天飞机支持创新（CASSI）试点项目的数据，探讨了公众对自动驾驶航天飞机扩展和安全性的看法。目的是了解影响公众支持或反对自动穿梭巴士扩张的因素，调查对安全的看法，并揭示不愿再次乘坐的原因。为此，本研究采用了秩相关分析、关联规则挖掘、中介分析和专题分析。研究发现，乘车后安全认知和再次乘车意愿等关键中介因素显著影响公众对班车扩建的支持度。此外，还强调了积极的初步经验、及时的服务和提高业务绩效对促进公众接受的重要性。总的来说，研究结果强调了解决安全问题、确保可达性和改善航天飞机运营以促进大规模采用的必要性。这项研究提供了有价值的见解，了解公众对安全和自动穿梭运营的意见，指导政策制定者和服务提供商更好地将这些车辆整合到城市交通系统中。

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引用次数: 0

Managing coexistence between taxis and ride-hailing services: A longitudinal case study of operational strategies and policy implications 管理出租车和叫车服务之间的共存：运营策略和政策影响的纵向案例研究

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2026-01-19 DOI: 10.1016/j.cstp.2026.101718

Tianqi Gu , Inhi Kim , Long Cheng

Digital ride-hailing platforms are transforming urban mobility and labor systems, challenging governments to integrate traditional and algorithmic workforces. This study investigates how taxi and ride-hailing drivers adapt to hybrid mobility systems, using a four-year longitudinal dataset from Suzhou, China covering both pre- and post-pandemic periods. We identify three behavioral strategies—Lion (ethics-driven), Fox (risk-calculative), and Horse (income-driven)—that describe how driver groups balance risk, income, and professional identity under different institutional and regulatory settings. The COVID-19 crisis served as a natural stress test, revealing contrasts in labor resilience: regulated taxi drivers maintained stability, while freelance and rental-based drivers experienced high withdrawal rates due to weak protections. These results highlight how institutional design and platform governance jointly shape operational behavior and labor adaptation. The findings provide actionable insights for designing inclusive, equitable, and crisis-resilient transport governance, and the proposed typology offers a transferable framework for understanding platform labor resilience beyond the Suzhou case.

数字叫车平台正在改变城市交通和劳动力系统，挑战政府整合传统和算法劳动力。本研究调查了出租车和网约车司机如何适应混合出行系统，使用了来自中国苏州的四年纵向数据集，涵盖了大流行前后的时期。我们确定了三种行为策略-狮子（道德驱动），福克斯（风险计算）和马（收入驱动）-描述了驾驶员群体如何在不同的制度和监管环境下平衡风险，收入和职业身份。新冠肺炎危机是一个自然的压力测试，揭示了劳动力弹性的差异：受监管的出租车司机保持稳定，而自由职业者和租赁司机由于保护不力而出现了很高的退出率。这些结果突出了制度设计和平台治理如何共同影响操作行为和劳动力适应。研究结果为设计包容、公平和危机弹性的交通治理提供了可操作的见解，提出的类型学为理解苏州案例之外的平台劳动力弹性提供了一个可转移的框架。

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引用次数: 0

The end of cheap flying? Decarbonization and capacity limits reshaping air travel growth in a mature market 廉价飞行的终结？脱碳和运力限制重塑成熟市场的航空旅行增长

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2026-01-18 DOI: 10.1016/j.cstp.2026.101717

Igor Davydenko , Gijsbert van Eck , Marco Kouwenhoven , Hans Hilbers

This paper presents a long-term forecast for the Dutch aviation sector up to 2060, analyzing the impacts of scenarios involving international demographic and economic development, European and global climate policy, and local airport capacity constraints. The availability of sustainable fuels is assessed for the global market. Using four distinct scenarios, combining two dimensions of high/low economic and demographic growth and fast / delayed climate transitions, the study models future air travel demand, aircraft movements at Amsterdam Airport Schiphol, energy requirements, and resulting CO₂ emissions. The modeling is conducted using the AEOLUS model, which relies on population and economic growth, alongside the costs of flying, to determine travel demand using, among other, income and price elasticities. The analysis reveals that in high-growth scenarios, unconstrained demand could lead to a doubling of aircraft movements to approximately 1 million per year at Schiphol by 2060. However, the current flight cap of 500,000 movements at Schiphol represents the most significant limiting factor, which would be reached before 2030 in these scenarios. This scarcity incentivizes airlines to deploy larger aircraft, allowing passenger numbers to increase even after the flight limit is met. All scenarios project a sharp decline in CO₂ emissions after 2030, driven by mandated blending of Sustainable Aviation Fuels (SAF) and efficiency gains. Consequently, a decades-long trend of falling airfares is expected to reverse, with ticket prices projected to rise across all scenarios due to higher fuel and carbon costs, compounded by capacity scarcity in high-growth scenarios.

本文提出了荷兰航空业到2060年的长期预测，分析了涉及国际人口和经济发展、欧洲和全球气候政策以及当地机场容量限制的各种情景的影响。对全球市场可持续燃料的可用性进行了评估。该研究使用四种不同的情景，结合经济和人口增长的高/低和气候变化的快/延迟两个维度，模拟了未来的航空旅行需求、阿姆斯特丹史基浦机场的飞机起降、能源需求以及由此产生的二氧化碳排放。建模是使用AEOLUS模型进行的，该模型依赖于人口和经济增长，以及飞行成本，以确定旅行需求，其中包括收入和价格弹性。分析显示，在高增长的情况下，不受约束的需求可能导致史基浦机场的飞机起降量翻倍，到2060年达到每年约100万架次。然而，目前史基浦机场50万架次的飞行上限是最重要的限制因素，在这些情况下，这一上限将在2030年之前达到。这种稀缺性促使航空公司部署更大的飞机，即使在达到飞行限制后，乘客数量也会增加。所有情景都预测，在强制性混合可持续航空燃料（SAF）和效率提高的推动下，2030年后二氧化碳排放量将大幅下降。因此，长达数十年的机票价格下降趋势预计将逆转，由于燃料和碳成本上升，加上高增长情况下运力不足，所有情况下的机票价格预计都将上涨。

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引用次数: 0

Transportation as the Vanguard—Dynamic evolution and spatial differentiation of local marine transportation policies in China 交通作为先锋——中国地方海上交通政策的动态演变与空间分异

IF 3.3 Q3 TRANSPORTATION

Case Studies on Transport Policy

Pub Date : 2026-01-15 DOI: 10.1016/j.cstp.2026.101714

Caizhi Sun, Jing Gao, Zhenan Yang

As a key driver of high-quality marine economic development, the maritime transport sector depends heavily on the role of local governments in policy design and implementation. This study examines maritime transport policies issued by local governments in China. Using analyses of policy quantity and intensity, LDA topic modeling, and policy instrument classification, we systematically analyze 1,685 policy documents from 11 coastal provincial-level regions. The study aims to identify the dynamic evolution and spatial differentiation of local maritime transport policies. The results reveal clear dynamic evolution patterns. First, over time, policy quantity and intensity follow a stepwise trajectory, progressing through four stages: embryonic, exploratory development, rapid development, and quality-optimization. Second, policy themes have shifted from an early focus on cargo transport and channel navigation toward safety supervision and pollution control, indicating a transition from extensive growth to sustainable governance. Third, although the use of policy instruments has increased, their structure remains imbalanced, characterized by strong environment-oriented, moderate supply-side support, and weak demand-side measures, with limited coordination and innovation. Distinct spatial differentiation patterns are also observed. Policy quantity and intensity show an uneven distribution, with strong concentration along the southeastern coast and weaker activity in northern and southern regions; the Yangtze River Delta and Pearl River Delta have emerged as major sources of policy innovation. Regional differences in economic development and resource endowments lead to divergent policy theme preferences. Across regions, policy instrument structures display a clear hierarchy—environment-oriented instruments dominate, followed by supply-side tools and then demand-side tools—suggesting that local governments prioritize regulatory frameworks and supervision in maritime transport governance. This study provides a methodological contribution to understanding the evolution of local maritime transport policies in China and offers practical insights for improving regional maritime transport governance.

作为海洋经济高质量发展的关键驱动力，海上运输部门在很大程度上依赖于地方政府在政策设计和实施方面的作用。本研究考察了中国地方政府发布的海上运输政策。采用政策数量与力度分析、LDA主题建模和政策工具分类等方法，对来自11个沿海省级地区的1685份政策文件进行了系统分析。本研究旨在识别地方海上运输政策的动态演变和空间分异。结果显示出清晰的动态演化模式。首先，从时间上看，政策的数量和力度是渐进式的，经历了萌芽阶段、探索性发展阶段、快速发展阶段和质量优化阶段。其次，政策主题已从早期的货物运输和航道航行转向安全监管和污染控制，表明从粗放型增长向可持续治理的转变。三是政策工具虽有所增加，但结构不平衡，表现为环境导向强、供给侧支持适度、需求侧措施薄弱、协调创新不足。空间分异格局也明显。政策数量和力度分布不均，东南沿海集中程度高，南北地区活跃程度较弱；长三角和珠三角已成为政策创新的主要来源。区域经济发展和资源禀赋的差异导致政策主题偏好的差异。在各个地区，政策工具结构显示出明确的等级结构——环境导向工具占主导地位，其次是供给侧工具，然后是需求侧工具——这表明地方政府在海上运输治理中优先考虑监管框架和监督。本研究为理解中国地方海上运输政策的演变提供了方法上的贡献，并为改善区域海上运输治理提供了实践见解。

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