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Route-based network analysis: “Route betweenness” and “route link density” applied to a study of a proposed bridge in Trondheim 基于路线的网络分析:“路线之间”和“路线连接密度”应用于特隆赫姆拟建桥梁的研究
IF 6.3 2区 工程技术 Q1 ECONOMICS Pub Date : 2025-11-26 DOI: 10.1016/j.jtrangeo.2025.104491
Peter Schön , Eva Heinen , Bendik Manum
There is growing recognition of the importance of cycling infrastructure in promoting cycling. However, established methods have a limited ability to predict the citywide effects of single infrastructure interventions on cycling. Network analysis provides a promising alternative; however, studies linking network measures to mode choice are rare. To address this gap, we applied two route-based network measures – route betweenness and the novel measure route link density – to evaluate the impact of the proposed bridge on cycling probabilities. Route betweenness measures the mean betweenness of shortest routes between origin–destination pairs, accounting for route connectivity, directness, and urban density. Route link density quantifies the mean density of network links along shortest routes. Using travel survey data, we trained a gradient boosting model to estimate cycling probabilities using route-based network measures and built environment variables at trip origins and destinations. We then applied the model to a synthetic population and estimated the changes in probability due to the bridge. The results show that route length and route-based measures are key features for predicting cycling probabilities. The models also reveal non-linear effects and notable feature interactions. When applied to a synthetic population, high route betweenness and moderate route link density increase the predicted probability of cycling. Conversely, low values can decrease probabilities, even when route lengths decrease. The effect of route betweenness is particularly strong, as the measure responds to the rerouting of trips over the bridge. Our findings highlight the importance of incorporating route-based measures in travel research and the need for longitudinal follow-up studies.
人们越来越认识到自行车基础设施对促进自行车运动的重要性。然而,现有的方法在预测单一基础设施干预对骑行的全市影响方面能力有限。网络分析提供了一个有希望的替代方案;然而,将网络措施与模式选择联系起来的研究很少。为了解决这一差距,我们采用了两种基于路线的网络测量方法——路线间隔和新颖的路线链路密度测量方法——来评估拟议的桥梁对循环概率的影响。路由之间度量的是出发地到目的地对之间最短路由的平均之间的距离,考虑了路由的连通性、直接性和城市密度。路由链路密度是指网络中沿最短路由的平均链路密度。利用旅行调查数据,我们训练了一个梯度增强模型,利用基于路线的网络措施和旅行起点和目的地的建成环境变量来估计骑行概率。然后,我们将该模型应用于一个合成总体,并估计由于桥而导致的概率变化。结果表明,路径长度和基于路径的度量是预测循环概率的关键特征。模型还揭示了非线性效应和显著的特征相互作用。当应用于合成种群时,高的路径间隔和中等的路径链接密度增加了预测的循环概率。相反,低的值可以降低概率,即使路由长度减少。路线之间的影响尤其强烈,因为该措施响应了过桥旅行的改道。我们的研究结果强调了在旅游研究中纳入基于路线的措施的重要性以及纵向后续研究的必要性。
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引用次数: 0
Assessing modal shift potential to ease port-city tensions: A case study for the port of Antwerp based on truck GPS data 评估模式转变的潜力,以缓解港口和城市之间的紧张关系:基于卡车GPS数据的安特卫普港案例研究
IF 6.3 2区 工程技术 Q1 ECONOMICS Pub Date : 2025-11-25 DOI: 10.1016/j.jtrangeo.2025.104493
Emma Ceulemans, Edwin van Hassel
The heavy reliance on trucking in port-hinterland transport causes significant environmental and societal issues for surrounding areas, straining the port-city relationship. To mitigate these impacts, shifting traffic to alternative hinterland transport modes, such as intermodal inland waterway transport, is essential. This study assesses the modal shift potential for observed port-hinterland container truck trips, derived from truck GPS data, by estimating generalised transport costs under varying road congestion scenarios and applying a logit mode choice model. Results indicate that 18 to 27.5 % of domestic port-hinterland container truck trips could shift to intermodal inland waterway transport under a one- to two-hour increase in road travel times, particularly from locations near inland terminals along three major traffic corridors linking the port of Antwerp to Liège, Brussels, and Kortrijk. Diverting these truck trips from the road network could reduce port-related highway traffic around the city of Antwerp by up to 6.5 %. These findings offer valuable guidance for policymakers, enabling targeted interventions at locations with the highest modal shift potential, thereby reducing trucking dependence and alleviating port-city tensions.
港口-内陆运输严重依赖卡车运输,给周边地区造成了严重的环境和社会问题,使港口-城市关系紧张。为了减轻这些影响,将交通转移到其他内陆运输方式,如多式联运内河运输,是必不可少的。本研究通过估计不同道路拥堵情况下的一般运输成本,并应用logit模式选择模型,评估了观察到的港口-腹地集装箱卡车旅行的模式转变潜力。结果表明,在公路行驶时间增加1至2小时的情况下,18%至27.5%的国内港口腹地集装箱卡车旅行可能会转向多式联运内河运输,特别是从连接安特卫普港到利弗里奇、布鲁塞尔和科特里克的三条主要交通走廊的内陆码头附近的地点。将这些卡车从公路网中转移出来,可以使安特卫普市周围与港口相关的高速公路交通量减少6.5%。这些发现为政策制定者提供了有价值的指导,使其能够在模式转换潜力最大的地点进行有针对性的干预,从而减少对卡车运输的依赖,缓解港口城市的紧张局势。
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引用次数: 0
Unravelling the spatial agglomeration patterns and drivers of the maritime service industry in the Yangtze River Delta 长三角海洋服务业空间集聚格局及驱动因素分析
IF 6.3 2区 工程技术 Q1 ECONOMICS Pub Date : 2025-11-25 DOI: 10.1016/j.jtrangeo.2025.104497
Shun Chen , Xingjian Wang , Louise Lu Li , Qiang Zhang
The maritime service industry serves as a critical catalyst for regional competitiveness and global supply chain integration. Despite its strategic importance, the micro-scale spatial agglomeration mechanisms of maritime service enterprises (MSEs) remain underexplored, particularly in rapidly evolving economic landscapes. Addressing this gap, this study investigates the spatiotemporal dynamics and determinants of MSE agglomeration in China's Yangtze River Delta (YRD), leveraging a dataset of 5968 MSEs classified into basic, auxiliary, and derivative services from 2000 to 2023. Results reveal a hierarchical pattern: Shanghai anchors high-value derivative services, while auxiliary and fundamental services decentralize to peripheries, shaped by economic, transportation, technological and financial factors. Spatial spillovers highlight interregional interdependence, requiring coordinated policies to balance specialization and synergy. The study advances maritime cluster analysis by developing a hierarchical analytical framework, unveils MSE agglomeration determinants and quantifies interregional spillovers. The research provides insights for adaptive governance, well-balanced and resilient development of maritime clusters.
海运服务业是区域竞争力和全球供应链一体化的重要催化剂。尽管具有重要的战略意义,但海洋服务企业(mse)的微观空间集聚机制仍未得到充分探索,特别是在快速变化的经济格局中。基于2000 - 2023年5968个中国长三角MSE的基本、辅助和衍生服务数据,研究了中国长三角MSE集聚的时空动态及其影响因素。研究结果显示,受经济、交通、技术和金融等因素影响,上海以高价值衍生服务为主,辅助和基础服务向周边分散;空间溢出效应强调区域间的相互依存,需要协调政策来平衡专业化和协同效应。该研究通过开发层次分析框架来推进海洋聚类分析,揭示了MSE聚集的决定因素,并量化了区域间溢出效应。该研究为海洋集群的适应性治理、均衡和弹性发展提供了见解。
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引用次数: 0
Engaging citizens from low-income communities in transport planning: experiences from peer research studies conducted in three African cities 让低收入社区的公民参与交通规划:来自三个非洲城市的同行研究的经验
IF 6.3 2区 工程技术 Q1 ECONOMICS Pub Date : 2025-11-24 DOI: 10.1016/j.jtrangeo.2025.104484
Gina Porter , Bradley Rink , Emma Murphy , Fatima Adamu , Plangsat Bitrus Dayil , Sam Clark , Bulelani Maskiti , Claire Dungey , Ariane de Lannoy
This paper draws on experience from a series of transport-focused studies built round peer research with community members resident in low-income neighbourhoods at the periphery of three major cities: Abuja, Cape Town and Tunis. These were conducted firstly with young women aged 18–35 in all three cities over a four-year period (2019–2022, i.e. spanning the pandemic), followed by a recently completed pilot with young men in the same age group (but in this case restricted to Cape Town). The paper reflects firstly on the peer research methodology employed (including training procedures, ethical issues and context specific challenges/barriers) and the significant field outputs achieved by the groups concerned through their in-depth interviews, participant observation and mobility diaries. It then moves on to consider the engagement of the community peer researchers with city transport professionals and practitioners at our project stakeholder consultative group meetings and their potential for promoting the design of more inclusive, accessible and sustainable transport systems. While peer researchers' direct field evidence offers rare insights into the transport and mobility challenges that many marginalised residents of these low-income neighbourhoods experience in the everyday – perspectives that could be crucial to effective user engagement around transport issues in an Urban Living Lab - the actual patterns and potentialities of engagement within each city that might promote a more socially just travel environment are strongly shaped by a range of locally specific factors. These extend from resource and policy contexts set within distinctive local urban geographies, to the personalities and positionality of all actors involved.
本文借鉴了一系列以交通为重点的研究的经验,这些研究围绕着对居住在阿布贾、开普敦和突尼斯三个主要城市外围低收入社区的社区成员的同行研究展开。这些研究首先在所有三个城市的18-35岁年轻女性中进行,为期四年(2019-2022年,即跨越大流行期间),然后在同一年龄组的年轻男性中进行了最近完成的试点(但在这种情况下仅限于开普敦)。本文首先反映了所采用的同行研究方法(包括培训程序、伦理问题和具体背景的挑战/障碍),以及相关群体通过深入访谈、参与者观察和流动日记取得的重要实地产出。然后,在我们的项目利益相关者咨询小组会议上,考虑社区同行研究人员与城市交通专业人员和从业人员的参与,以及他们促进设计更具包容性、可达性和可持续性的交通系统的潜力。虽然同行研究人员的直接现场证据为这些低收入社区的许多边缘化居民在日常生活中遇到的交通和流动性挑战提供了罕见的见解——这些观点对于城市生活实验室中有效的用户参与交通问题至关重要——但每个城市参与的实际模式和潜力可能会促进更社会公正的旅行环境,这在很大程度上受到一系列当地具体因素的影响的因素。这些因素包括在独特的地方城市地理范围内设置的资源和政策背景,以及所有参与者的个性和位置。
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引用次数: 0
Spatiotemporal dynamics of local transport greenhouse gases using mobile phone data: A framework for emissions estimation, allocation, and determinants identification 利用移动电话数据的本地运输温室气体时空动态:排放估算、分配和决定因素识别的框架
IF 6.3 2区 工程技术 Q1 ECONOMICS Pub Date : 2025-11-22 DOI: 10.1016/j.jtrangeo.2025.104492
Xianghui Zhang , Tao Cheng , Zijing Yang
Estimating and allocating greenhouse gases (GHGs) emissions from transport at the urban scale is essential for guiding local decarbonisation strategies and enabling effective carbon governance. However, conventional top-down methods often obscure the spatial, temporal, and behavioural complexity of urban mobility, limiting the design of targeted interventions. This study presents a novel bottom-up framework that leverages individual-level mobile phone data to estimate, allocate, and analyse transport-related GHG emissions at high spatial and temporal resolution. The framework supports multiple accounting perspectives, including territorial and residence-based principles, while enabling contributor tracing by traveller types and the identification of localised emission determinants. Applied to Greater London, the framework reveals significant shifts in emission patterns between pre- and post-pandemic periods, highlighting increased emissions from residents and trip-attracted individuals, alongside persistent dominance by pass-through travellers. It also captures how behavioural changes, such as remote work, have reshaped emissions determinants. The proposed approach provides a scalable and policy-relevant tool to support localised climate action and lays a foundation for evidence-based transport carbon trading systems.
在城市尺度上估算和分配交通运输产生的温室气体排放对于指导地方脱碳战略和实现有效的碳治理至关重要。然而,传统的自上而下的方法往往模糊了城市交通的空间、时间和行为复杂性,限制了有针对性干预措施的设计。本研究提出了一个新颖的自下而上的框架,利用个人层面的移动电话数据在高时空分辨率下估计、分配和分析与运输相关的温室气体排放。该框架支持多种核算视角,包括基于地域和居住地的原则,同时能够按旅行者类型追踪贡献者,并确定当地的排放决定因素。应用于大伦敦地区,该框架揭示了大流行前后排放模式的重大变化,突出显示居民和吸引旅行的个人的排放量增加,以及过境旅行者持续占主导地位。它还捕捉到了远程工作等行为变化如何重塑了排放决定因素。拟议的方法提供了一个可扩展的、与政策相关的工具,以支持地方气候行动,并为基于证据的运输碳交易系统奠定了基础。
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引用次数: 0
Assessing emergency medical services (EMS) accessibility before and after road pricing: A dynamic 2SFCA approach 道路收费前后紧急医疗服务可及性评估:动态2SFCA方法
IF 6.3 2区 工程技术 Q1 ECONOMICS Pub Date : 2025-11-22 DOI: 10.1016/j.jtrangeo.2025.104489
Zhiran Huang , Yi Sun
Road pricing has been regarded as an effective tool for mitigating traffic congestion in cities. It could, however, exacerbate inequity through negative externalities. This study compares accessibility to emergency medical services (EMS) before and after the road pricing policy in Hong Kong. We develop a dynamic two-step floating catchment area (2SFCA) method to account for changes in speed. The spatio-temporal patterns of changes in EMS accessibility are captured. Results show that while the maximum EMS accessibility values increased after the policy, the average values decreased, particularly during the morning peak, which indicates a polarisation effect. Global Moran's I analysis informs that EMS accessibility changes are spatially clustered, and bivariate local Moran's I reveals that improvements in EMS accessibility are associated with areas with high elderly population density. Sensitivity analysis further supports our findings. Findings highlight the horizontal inequity and vertical equity in relation to the policy, bridging the gap between road pricing and public health literature. Policy implications are discussed.
道路收费被认为是缓解城市交通拥堵的有效工具。然而,它可能通过负面外部性加剧不平等。本研究比较香港道路收费政策实施前后的紧急医疗服务可及性。我们开发了一个动态的两步浮动集水区(2SFCA)方法来解释速度的变化。分析了城市环境服务可达性的时空变化规律。结果表明:政策实施后,EMS可达性最大值增加,但平均值下降,特别是在早高峰期间,表现出极化效应;全球Moran’s I分析表明,EMS可达性变化具有空间聚类性,双变量局部Moran’s I分析表明,EMS可达性的改善与老年人口密度高的地区有关。敏感性分析进一步支持了我们的发现。调查结果强调了与政策相关的横向不平等和纵向公平,弥合了道路收费与公共卫生文献之间的差距。讨论了政策影响。
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引用次数: 0
Spatiotemporal prediction of transportation hub passenger distribution with sparse observation data: A pedestrian dynamics-informed deep learning approach 基于稀疏观测数据的交通枢纽客流分布时空预测:基于行人动态的深度学习方法
IF 6.3 2区 工程技术 Q1 ECONOMICS Pub Date : 2025-11-21 DOI: 10.1016/j.jtrangeo.2025.104490
Shulin He , Xinran Ju , Wendong Chen , Da Lei
Accurate prediction of passenger distribution in transportation hubs is essential for effective management, operational planning, and passenger experience optimization. However, complex spatial layouts and limited data availability of transportation hubs pose significant challenges to conventional prediction methods. This study proposes a Pedestrian Dynamics-informed Spatiotemporal Hypergraph Attention Network (PD-STHGAT) to address passenger distribution prediction under sparse monitoring conditions in transportation hubs. The model comprises two modules: a pedestrian dynamics module and a deep learning module. The pedestrian dynamics module represents passenger distribution in transportation hubs as a macroscopic streamline network. It embeds prior knowledge to support flow interpolation and contributes to a semi-supervised loss formulation. The deep learning module integrates Hypergraph Attention Networks (HGATs) and Gated Recurrent Units (GRUs). These components consider high-order spatiotemporal dependencies of passenger flow along the streamlines and provide hub-wide distribution predictions. A transportation hub scenario with simulated data is used to evaluate model performance. PD-STHGAT consistently outperforms baseline models in Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Weighted Mean Absolute Percentage Error (WMAPE), validating the effectiveness of integrating pedestrian dynamics prior knowledge to solve sparse data prediction problems. Beyond performance improvement, the proposed framework offers actionable insights that support dynamic operational decisions, resource allocation, and passenger guidance strategies within transportation hubs.
准确预测交通枢纽的客流分布对有效管理、运营规划和优化乘客体验至关重要。然而,交通枢纽复杂的空间布局和有限的数据可用性对传统的预测方法提出了重大挑战。本研究提出一个行人动态信息时空超图注意力网络(PD-STHGAT)来解决交通枢纽稀疏监测条件下的乘客分布预测问题。该模型包括两个模块:行人动力学模块和深度学习模块。行人动力学模块将交通枢纽的乘客分布表示为宏观流线网络。它嵌入先验知识来支持流量插值,并有助于半监督损失公式。深度学习模块集成了超图注意网络(HGATs)和门控循环单元(gru)。这些组件考虑沿流线的客流的高阶时空依赖性,并提供枢纽范围的分布预测。使用一个具有模拟数据的交通枢纽场景来评估模型的性能。PD-STHGAT在平均绝对误差(MAE)、均方根误差(RMSE)和加权平均绝对百分比误差(WMAPE)方面始终优于基线模型,验证了整合行人动态先验知识解决稀疏数据预测问题的有效性。除了性能改进之外,拟议的框架还提供了可操作的见解,支持交通枢纽内的动态运营决策、资源分配和乘客引导策略。
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引用次数: 0
Non-linear impact of built environment on metro-bike integration from an eye-level perspective: A deep learning approach with street view images 基于视觉水平视角的建筑环境对地铁自行车整合的非线性影响:街景图像的深度学习方法
IF 6.3 2区 工程技术 Q1 ECONOMICS Pub Date : 2025-11-19 DOI: 10.1016/j.jtrangeo.2025.104485
Shuli Luo , Lurong Xu , Sui Tao , Xiao Fu
The integration of metro and bike systems has emerged as a promising climate change mitigation strategy, fostering a transition towards sustainable transportation modes within urban landscapes. Extensive research has probed the effects of neighborhood-level built environment factors such as accessibility, urban density, land use mix, and proximity to cycling infrastructure—on cycling behavior. However, the impact of eye-level built environment features, those physical and visual characteristics of urban spaces as perceived by individuals at street level, remains insufficiently explored. Using Generalized Additive Mixed Models (GAMM), we examine the effects of both neighborhood-level and eye-level built environment variables on first-mile and last-mile metro-bike integration trips during weekdays and weekends, accounting for spatial and temporal autocorrelations. The results reveal that commercial establishments, job opportunities, population density, and spatial and temporal dynamics all significantly influence metro-bike integration. Surprisingly, the presence of cycle lanes shows a weak effect on integrated metro-bike usage. In addition, non-linear relationships are observed between metro-bike usage and eye-level built environment variables such as sky ratio, greenery, and building ratio, indicating the existence of optimal levels for improving metro-bike integration. The findings emphasize the importance of considering eye-level urban aesthetics when planning for transport infrastructures and thereafter provide concrete threshold guidelines for urban planners and policymakers to better integrate cycling facilities with metro system.
地铁和自行车系统的整合已经成为一种有希望的气候变化缓解策略,促进了城市景观向可持续交通模式的过渡。广泛的研究探讨了可达性、城市密度、土地利用组合和与自行车基础设施的接近性等社区级建筑环境因素对骑行行为的影响。然而,人眼水平的建筑环境特征的影响,即人们在街道水平感知到的城市空间的物理和视觉特征,仍然没有得到充分的探索。利用广义加性混合模型(GAMM),我们研究了社区水平和眼水平的建筑环境变量对工作日和周末第一英里和最后一英里地铁自行车整合出行的影响,并考虑了空间和时间的自相关性。结果表明,商业场所、就业机会、人口密度和时空动态对城市自行车整合有显著影响。令人惊讶的是,自行车道的存在对综合地铁自行车使用的影响很弱。此外,我们还观察到地铁自行车的使用与目视水平的建筑环境变量(如天空比、绿化和建筑比)之间存在非线性关系,这表明存在改善地铁自行车整合的最佳水平。研究结果强调了在规划交通基础设施时考虑城市美学的重要性,并为城市规划者和决策者提供了具体的阈值指导,以更好地将自行车设施与地铁系统结合起来。
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引用次数: 0
Decoding built environment impacts and regional interdependence of urban traffic emissions using interpretable deep learning 使用可解释深度学习解码建筑环境影响和城市交通排放的区域相互依存关系
IF 6.3 2区 工程技术 Q1 ECONOMICS Pub Date : 2025-11-18 DOI: 10.1016/j.jtrangeo.2025.104487
Boting Qu , Fen Li , Yuan Gao
Understanding the relationship between the built environment and traffic carbon emissions is essential for sustainable urban development. However, accurately modeling these relationships presents complexities, including capturing intricate spatial interdependencies, modeling dynamic factors, and fully accounting for crucial upstream emissions from electric vehicles (EVs). In this paper, a deep learning Spatiotemporal Graph Convolutional Network (ST-GCN) framework is proposed. Using Xi’an taxi GPS data, the well-to-wheel (WTW) carbon emissions for Electric Taxis (ETs) and Internal Combustion Engine Taxis (ICETs) are first quantified, respectively. These emissions are then modeled in ST-GCN by integrating static built environment, dynamic time-series, and external temporal factors. Utilizing the Integrated Gradients interpretation method, the complex mechanisms influencing emission patterns are identified. Findings reveal distinct ET/ICET emission characteristics and driving mechanisms, spatial heterogeneity, spillover effects, and how neighbor interactions jointly shape emission outcomes. This framework offers insights for accurate, equitable, and synergistic urban emission mitigation policies.
了解建筑环境和交通碳排放之间的关系对于可持续城市发展至关重要。然而,准确地模拟这些关系存在复杂性,包括捕获复杂的空间相互依赖性,模拟动态因素,以及充分考虑电动汽车(ev)的关键上游排放。本文提出了一种深度学习时空图卷积网络(ST-GCN)框架。利用西安出租车GPS数据,首先对电动出租车(ETs)和内燃机出租车(ICETs)的井到轮(WTW)碳排放量进行了量化。然后通过综合静态建筑环境、动态时间序列和外部时间因素,在ST-GCN中模拟这些排放。利用综合梯度解释方法,确定了影响辐射模式的复杂机制。研究结果揭示了不同的ET/ICET排放特征和驱动机制、空间异质性、溢出效应以及邻国相互作用如何共同影响排放结果。该框架为制定准确、公平和协同的城市减排政策提供了见解。
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引用次数: 0
Spatio-temporal characteristics and related factors of urban on-street parking violations: A nonlinear perspective 城市街道停车违法时空特征及影响因素:一个非线性视角
IF 6.3 2区 工程技术 Q1 ECONOMICS Pub Date : 2025-11-18 DOI: 10.1016/j.jtrangeo.2025.104486
Keliang Liu , Jian Chen , Wu Li , Rui Li , Qi Chen
Urban on-street parking violations pose significant challenges to traffic efficiency, safety, and urban management. Identifying their spatio-temporal characteristics and related factors is essential for developing effective governance strategies. However, existing studies have predominantly relied on linear analytical frameworks, and coupled with the limitations of non-continuous data, it is often difficult to capture the objective patterns of parking violations. To address this gap, this study examined 41,344 consecutive records of parking violations collected by monitoring devices over a two-month period. Twenty-two potential influencing factors were extracted from three perspectives: land use, parking supply, and road design. A combination of spatio-temporal analysis methods—including the standard deviational ellipse, hierarchical clustering, and dynamic time warping—was used to reveal the distribution and temporal patterns of parking violations. Furthermore, a gradient boosting decision tree model enhanced by an improved genetic algorithm (IGA-GBDT) was developed to jointly optimize feature selection and hyperparameters, enabling the exploration of nonlinear relationships between violations and their determinants. The results indicate that parking violations are more frequent on weekdays than weekends, with clear peaks during commuting hours. Weekday patterns follow an “expansion–stabilization–contraction” trend, and four distinct temporal clusters were identified across different locations. The IGA-GBDT model reveals nonlinear threshold effects of built environment and road design factors, as well as spatial heterogeneity in their influence on violations. This study provides a new perspective for on-street parking management and offer practical implications for more targeted and adaptive strategies.
城市街道停车违法行为对交通效率、交通安全和城市管理构成了重大挑战。确定其时空特征和相关因素对于制定有效的治理策略至关重要。然而,现有的研究主要依赖于线性分析框架,加上非连续数据的限制,往往难以捕捉停车违规的客观模式。为了解决这一差距,这项研究检查了监测设备在两个月内收集的41,344个连续违规停车记录。从土地利用、停车供应和道路设计三个角度提取了22个潜在影响因素。采用标准偏差椭圆、分层聚类和动态时间扭曲等时空分析方法,揭示了违规停车的时空分布规律。在此基础上,提出了一种基于改进遗传算法(IGA-GBDT)的梯度增强决策树模型,对特征选择和超参数进行联合优化,探索违规与其决定因素之间的非线性关系。结果表明,工作日违规停车频率高于周末,且高峰时段明显。工作日模式遵循“扩张-稳定-收缩”的趋势,在不同的地点发现了四个不同的时间集群。IGA-GBDT模型揭示了建筑环境和道路设计因素的非线性阈值效应,以及它们对违规行为影响的空间异质性。该研究为道路停车管理提供了新的视角,并为制定更有针对性和适应性的管理策略提供了实践启示。
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