基于非直线系数阻抗模型的公交车可达性研究

目前主流的路线推荐方法先通过寻径算法在满足各种约数条件下寻找K条可行路线，然后根据乘客的出行偏好从K条可行路线中选择一条路线推荐给乘客。然而，由于寻径算法的约束条件只能通过实时计算得到K条可行路线，当同时进行大量乘客的路线推荐时，由于无法快速获得推荐路线从而影响乘客的用户体验。因此本文提出基于离线关键站点的K最短时间算法，通过构造关键站点图和哈希表离线辅助查找K条最短路径，从而降低算法的时间复杂度。此外，通过分析发现，乘客对出行的负面感受与地铁换乘次数及拥挤度间并不是简单的线性关系，随着换乘次数和拥挤度的增加，乘客对出行的满意度会迅速衰减，所以，目前通过最大最小值方法计算出的乘客偏好路线并不一定是最佳路线。因此，本文设计了基于路径阻抗的地铁路线推荐方法，其中路径阻抗由不同权重的地铁时间成本和拥挤成本组成，通过计算K条最短时间路径的路径阻抗，从中选出符合乘客偏好的出行线路推荐给乘客。通过理论分析，随着查询次数的增多，本文提出的基于离线关键站点的K最短时间算法时间复杂度要远小于其他约数条件下的寻径算法。最后通过具体的实验示例验证本方法完全可以满足不同乘客的路线推荐需求。

在评价交通服务系统中，时空可达性是重要考虑因素，基于时空可达性的交通数据分析，能为决策者在路段建设及公共交通路线设计方面提供合理意见，有助于提高出行者到活动地点的便利程度。本文首先针对城市基础交通网络，从时空棱柱理论框架中构建时空网络，考虑个体在起点及活动地点所受的时间约束及费用约束，构建基于时空可达性交通网络模型，并将该模型进行改进，应用于城市公共交通系统中。并针对模型特点，设计深度遍历算法，得到时空网络中所有的可行路径，从中选出最优解。为更好地适应大规模路网，又设计拉格朗日松弛算法，通过其耦合约束和难约束，将原问题分解为最短路问题及背包问题，并更新拉格朗日乘子协调各子问题。最后，以实际问题为例，验证了模型和算法的合理性。研究结果表明本文提出的模型能有效解决以个体出行需求为目标的交通网络设计问题。

作为全国热门冰雪旅游目的地，哈尔滨2024年冬季接待游客超2000万人次，地铁日客流强度多次位列全国第一。然而，哈尔滨的交通系统在冬季旅游高峰期面临巨大压力，存在交通流量分布不均、停车难题显著、公共交通运力不足、道路通行受冰雪天气制约等问题。本文以酒店、地铁、景区的空间分布与衔接关系为切入点，结合文献分析与实地数据，提出当前景区、酒店的不同交通区位特征及问题，并构建差异化交通解决方案，包括地铁环线微循环系统、“地铁 + 微型接驳车”循环模式、地下通道网络与多功能枢纽建设，以及智能调度与动态除冰系统的引入。研究结果表明，这些策略能够有效缓解冬季交通压力，提升游客出行体验，并推动绿色交通发展。未来研究应进一步结合寒地气候特点，探索公共交通与旅游体验的互动关系，提出更具针对性的交通优化方案。

互联网租赁自行车是解决城市公共交通“最初和最后一公里”问题的方式，同时也吸引了一部分城市公共交通客流，与公共交通存在竞争和合作关系，对城市公共交通的发展产生了影响。然而，关于公共交通和互联网租赁自行车的影响模式还需要科学地讨论，尤其是量化其影响程度。本研究首先分析了互联网租赁自行车和城市公共交通的服务特点，并从时间和空间两个方面分析了互联网租赁自行车和城市公交之间的竞争、合作和补充关系。然后，本研究基于昆明市的共享单车骑行大数据，对这些关系进行了定量比较分析，得出了竞争与合作的关系。结论是，在昆明市，互联网租赁自行车和城市公共交通的合作关系比例大于竞争关系，且可以弥补城市公共交通运营时间和覆盖空间的不足。

随着城市交通压力的加大，小区开放的话题也越来越多地被提及。本文通过研究交通灯对交通的干扰程度，不同类型的车辆在交叉口的不同状态和不同路段交通拥挤程度等指标，建立速度–车辆密度模型。通过比较不同时期同一段道路的车流量，可知小区开放后车辆通行数量增加，缓解了交通压力，既提高了区域路网密度又提高了交通可达性；在考虑延误时间和二次排队率的基础上，在小区规划中引入公交，并通过优化小区选址、合理规划小区内部道路结构，增加小区内部道路和外围道路的协调性。

可达性是衡量居民能否便捷地享受公园绿地的重要标准。本文以邯郸市主城区为研究范围，将多源数据纳入高斯两步移动搜索法，计算居民到公园绿地的可达性；以局部莫兰指数识别可达性薄弱地区。结果表明：邯郸市公园绿地可达性空间分布不均衡，形成城区中心与西南两个圈层递减区域；可达性低值聚类区域位于城区北部与正南侧，是公园绿地选址设计应重点关注的地区。研究结果可精准识别公园绿地短缺区域，为城市公园绿地的选址设计提供一定的科学建议及参考。

公交线网评价作为衡量城市可持续发展的重要指标，是推动城市高质量发展的关键因素。精确的公交线网分析评价，对于评估城市发展进程、城市道路空间品质以及城市交通研究具有重要的价值和意义。文章将以大连市金普新区为例，通过高德地图获取公交线网、站点相关数据，以《公共汽电车线网评价指标》(JT/T 1457-2023)为主要评价标准并基于GIS进行空间分析，根据相应情况将研究区域分别以街道、格网作为评价单元，并基于GIS软件将分析结果进行可视化。结果显示：大连市金普新区公交线网及站点整体分布不均；公交线路总长度不足；公交站点覆盖率不足，生活服务覆盖率不够均衡；部分线网非直线系数需进一步优化。该研究结果可为进一步优化金普新区公交线网从而促进金普新区可持续发展提供科学支撑。

随着城市化进程的加速，城市交通拥堵问题日益严重，已成为制约城市应急响应效率的核心因素。应急物流车辆在复杂的城市路网中快速通行是确保应急救援成功的关键。然而，传统路径规划方法多基于静态路网的最短距离原则，忽略了交通流量波动、信号控制策略以及车辆行为等动态因素，导致规划路径在实际场景中频繁陷入拥堵，无法满足应急响应的高效性需求。为解决这一问题，本文提出一种融合交通流动态特性、信号控制优化及车辆行为模型的综合路径规划方法。该方法通过图论理论构建加权路网模型，将城市道路网络抽象为一个由节点(交叉口)和边(道路)组成的加权有向图，并引入交叉口不等待通行概率作为路径代价函数的重要组成部分。在此基础上，本文对经典的Dijkstra算法进行改进，以实现多目标路径优化，同时兼顾路径的最短时间和交通信号优化原则。实验部分，本文采用3 × 3网格型路网进行模拟验证，设置了一系列与交通流量、信号控制及车道通行能力相关的参数。结果表明，该方法能够有效规避高流量路段，使总行程时间降低18.7%，交叉口平均等待时间减少23.5%。此外，通过引入交通信号相位、车道通行能力及转向行为等因素，路径规划结果更加贴合实际交通环境，显著提高了应急车辆的通行效率和应急响应速度。综上所述，本文提出的基于交叉口不等待概率的路径规划方法为智能交通系统与应急物流管理提供了理论支持与实践参考。

本文研究了大型活动下终点停车资源在不同出行需求产生区的最优分配问题。大型活动停车规划的组织方做出停车券分配后，用户会选择合适的出行方式，并根据交通流状态进行出行路径决策，使其出行成本最小。将大型活动周边停车资源的有限性和出行者的出行方式选择行为结合起来，最优停车券分配问题可以描述为一个双层规划模型。其中，下层规划是考虑了停车券约束的logit多用户方式划分均衡模型，并构建了等价的凸规划模型，上层规划的目标是最小化系统的总出行成本。最后，通过算例验证了模型的有效性，表明停车券分配策略可以提高公共交通的分担率，同时减少活动周边的路段拥堵。

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The outbreak of COVID-19 caused unprecedented declines in public-transport use. As travel frequencies rebound, ridership is recovering, although it remains considerably below pre-pandemic levels. This study compares pre-to post-pandemic public-transit use among workers and non-workers, and the changing impact of local and regional accessibility. Additionally, we assess the impact of increased telecommuting on workers ’ transit use before, during, and after the pandemic. We estimate two weighted multilevel linear regressions using a three-wave panel survey over the years 2019 – 2022 in Montr ´ eal, Canada. Results indicate that the factors that determine workers ’ and non-workers ’ transit patterns have tended to diverge after the pandemic. For workers, the relevance of accessibility in promoting utilitarian transit use considerably decreased, being responsible for close to 10% of the post-pandemic transit-use reduction. The increase of telecommuting frequency due to the pandemic contributed more than 10% of the post-pandemic transit-use reduction, but the effect of transit commuting time has remained relevant. For non-workers, the effect of regional accessibility by transit has increased after the pandemic, which has partly mitigated non-workers ’ transit-use decline. Moreover, we find there is a joint effect of local and regional accessibility that has maintained after 2019 for non-workers. Results from this work have relevant implications for transit planners and policymakers. To help transit-use recovery, results suggest that providing good transit connection to the workplace promotes workers ’ transit use, while promoting transit accessibility in lower-local-accessibility areas is key for non-worker transit ridership.

Direct-demand models (DDM) are increasingly being used for a diversity of transit research and practice purposes. Yet few station-level DDM studies have explored the use of composite indicators of metropolitan accessibility in predicting demand. After all, provision of access to metropolitan destinations is one of the main goals of rapid-transit systems. Furthermore, to this author ’ s knowledge no study has explored potential interactions with local-level accessibility indicators that are typically included in station level transit DDMs. This study explores these possibilities and uses Los Angeles multimodal rapid-transit network as a representative case study of a system that operates in a dispersed agglomeration where multiple sub-centers are linked. Multi-level generalized linear models were implemented where key predictors, including stations ’ metropolitan-and a local-accessibility indicators are regressed onto average weekday boardings. Furthermore, more general accessibility constructs were developed via EFA and implemented in models; and parameters non-stationarity was assessed via geographically weighted regressions. Results indicate that nodal metropolitan accessibility is a significant predictor of patronage in LA ’ s rapid-transit network, and that its interaction with local-accessibility amplifies boardings and improves DDM models ’ explanatory power. More general constructs of accessibility at metropolitan and local-scale were derived via EFA and these resulted in a more parsimonious model with equal predictive power. Land-use and transit planners would benefit from including an accessibility lens in their DDM modeling. Practical applications of these type of models include TOD scenario planning, comparative route alignment studies, system expansion studies, and for didactic purposes given the ability of accessibility measures to capture land-use/transportation interactions.

ABSTRACT Daily activity complexity—the diversity and sequence of activities individuals perform—is crucial for understanding travel behavior. However, the non-linear spatial interactions of socio-demographic and land use factors influencing this complexity remain less explored. This study integrates a complexity indicator (encompassing entropy and activity transitions), spatial clustering (Local Indicators of Spatial Association), and random forest modeling to address this gap. Using the 2018 Okanagan Travel Survey data, we identify distinct spatial clusters: High-High (areas where individuals and their neighbors both exhibit high complexity), High-Low, Low-Low, and Low-High complexity. Our results highlight significant non-linear associations between daily activity complexity and factors such as proximity to central business districts, amenities, transit accessibility, land use diversity, age, and income. This combined approach captures intricate spatial interactions, providing novel insights into how activity complexity varies across different geographic and socio-demographic contexts, emphasizing the importance of considering non-linear effects in travel behavior analysis.

Abstract. This study investigates the key factors influencing public transport mode shares in Uyo Urban area, Akwa Ibom State, Nigeria, with a focus on understanding the role of the built environment factors on public transport mode shares. The study employed a mixed-method approach, utilizing a structured survey for data collection, capturing key variables such as population density, transit supply, road network density, and commuter preferences. Data were analyzed using Principal Component Analysis (PCA), Multiple Linear Regression, and Geographically Weighted Regression (GWR) to explore spatial and non-spatial relationships between the identified factors and public transport usage. The PCA revealed three key components influencing public transport mode share: accessibility and infrastructure quality (39.36%), environmental constraints (15.15%), and mobility and Travel behaviour (13.15%). Regression analysis indicated that environmental constraints were the most significant predictor, followed by mobility and travel behaviour and accessibility and infrastructure quality. The GWR analysis highlighted spatial heterogeneity, showing that the impact of these factors varied across different neighbourhoods within Uyo urban. The findings suggest that improving infrastructure, addressing environmental constraints, and aligning public transport systems with commuter behaviours are crucial for increasing public transport usage. Policy recommendations include enhancing transit supply, improving road connectivity, mitigating environmental challenges, and tailoring services to commuter needs. The study underscores the importance of a multi-faceted approach to public transport planning that considers both infrastructure and socio-environmental factors to improve public transport adoption and sustainability in Uyo Urban and similar urban contexts.

The global trend toward urbanization has spurred the widespread adoption of transit-oriented development (TOD). While previous research has extensively explored the relationship between land use and TOD ridership, much of it has focused on linear associations at a singular scale. Leveraging recent advancements in nonlinear modeling and the accessibility of open-source data, this study employs a comprehensive two-step methodology. Firstly, K-means clustering algorithm categorizes TOD sites in Shenzhen into three distinct clusters, providing a site-based understanding of their characteristics. Subsequently, a Light Gradient Boosting Machine (LightGBM) classification model, complemented by SHapley Additive exPlanations (SHAP) values for interpretation, quantitatively evaluates the influence of mixed land use on TOD ridership across various catchment areas. As for the findings, we discover that land-use factors have different effects on TOD site patronage at different buffer radii and delve into the intricacies of these effects. Further results reveal non-linear relationships with varying degrees of positivity and negativity. For instance, residents and health sites positively impact patronage across all buffer radii, while certain commercial land uses exhibit a negative influence. The study demonstrates how the importance of different land-use structures varies across these clusters, shedding light on the nuanced impacts of land use on TOD catchment areas. Our research optimizes land-use mixes based on predominant cluster characteristics by offering actionable recommendations for urban managers.

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Classifying a time series is a fundamental task in temporal analysis. This provides valuable insights into the temporal characteristics of data. Although it has been applied to traffic flow and individual-centered accessibility analysis, it has yet to be applied to place-centered accessibility research. In this study, we have proposed an actual isochrone and dynamic time-wrapping distance-based k-medoids method and tested its applicability to a bus accessibility analysis. Using bus floating car data, our method calculated the actual isochrone area as an accessibility measurement and constructs an accessibility time series for each hexagonal geographical unit within the area of interest. We then calculated the dynamic time warp distance between the accessibility time series of pairwise geographical units and used these distances for k-medoid clustering. The optimized class number k was selected by considering the elbow method, silhouette score, and human examination. Our case study in Hefei, China demonstrates the feasibility of our method for accessibility time series classification. We also discovered that the resulting classes follow clear spatial patterns, indicating that different time series classes may be correlated with their spatial location. To our knowledge, this is the first time that such a classification method has been applied to place-centered accessibility time series analysis. Our data-driven method can inform place-centered accessibility in an era in which large quantities of spatiotemporal data like floating car data are available.

Suroboyo Bus and Trans Semanggi Suroboyo are public modes in Surabaya City, should be one way to serve city mobility in high number. However, the load factor of the city bus is below 50%. Therefore, it is necessary to evaluate the provision of public transportation, such as the city bus accessibility. This study uses the Public Transport Accessibility Levels (PTAL) method to analyze the city bus accessibility. The analysis result shows that most of the city bus accessibility levels are in the very poor category. This means that the city bus system could cover the city area at low level. Following that, the relationship between the accessibility level and the transit ridership is analyzed using correlation analysis. The results show that there are a significant correlation between the variable number of passengers and the bus stop accessibility index; frequency with the purpose of travel; accessibility index with the distance variable (distance of the departure stop from the origin location; distance of the destination stop to the destination location; distance traveled from the departure stop to the destination stop and total mileage); the frequency with the socioeconomic variables (age; average monthly income and driving license ownership). Based on these results, some recommendations are proposed to increase the accessibility level for influencing the demand of city bus.

In this paper we explore and compare various techniques for the calculation of distance decay parameters which are estimated using statistical methods with half-life decay parameters which are derived mathematically. Half-life models appear to be a valid alternative to traditional spatial interaction models, especially in the presence of spatially highly disaggregate data. Our results indicate that Half-life models are more accurate for the construction of decay parameters than are unconstrained spatial interaction models in ‘medium’ sized datasets but not as accurate as doubly-constrained models. However, using highly detailed and disaggregate datasets Half-life models may be viable alternatives to doubly-constrained spatial interaction models as the latter will be difficult to estimate when the number of origins and destinations increase. In addition, Half-life models rise in accuracy with increasing degrees of disaggregation due to reductions of systematic errors between observed individual level commuting distance and modelled distances between origins and destinations. In sum, our findings are as follows. First, since unconstrained and doubly-constrained spatial interaction models become increasingly difficult to estimate and/or less accurate to use compared to Half-life models as the spatial disaggregation increases choice of decay parameter estimation model should be considered in relation to level of disaggregation. Secondly, Half-life models are not affected by the systematic errors observed in the statistically derived models. Finally, using Half-life models for the estimation of decay parameters is simple which may make it easy to employ among practitioners lacking skills or computer means for the estimation of more complex statistically derived models.

The last kilometer connection problem of metro transit stations is the core factor to measure the connection efficiency and service quality. Establishing the spatiotemporal distribution pattern of the connection distance is conducive to clarifying the interaction mechanism between bike-sharing connections and urban space. This study focuses on the travel behavior of shared bicycle users accessing metro stations, aiming to reveal the access distance decay patterns and their relationship with influence factors. Finally, the random forest algorithm was used to explore the nonlinear relationship between the influencing factors and the connection decay distance, and to clarify the importance of the factors. Multiple linear regression was applied to examine the linear correlation between the distance decay coefficient and the factors influence. The geographically weighted regression was further employed to explore spatial variations in their effects. Finally, the random forest algorithm was used to rank the importance of the impact factors. The results indicate that proximity distance to metro stations, proximity distance to bus stops, and the number of bus routes serving the station area have significant negative correlations with the distance decay coefficient. Significant spatial heterogeneity was observed in the influence of each factor on the distance decay coefficient, based on the geographically weighted regression analysis. With a high goodness-of-fit (R2 = 0.8032), the Random Forest regression model furthermore quantified the relative importance of each factor influencing the distance decay coefficient. The findings can be directly applied to optimize the layout of shared bicycle parking, metro access facilities planning, and multi-modal transportation system design.

Public transport infrastructure creates the effect of agglomeration through transportation externalities. Effective density is an accessibility based agglomeration that was raised as a positive externality from public transportation investments. The aim of this paper is to understand whether public transport facility would induce agglomeration around stations and furthermore induce train ridership. A methodology was developed to reveal the causality of effective density on ridership and reduce the confounding effects from land use-related determinant factor. This was shown by the propensity score matching that tested if effect of a station being in the treatment group (high effective density stations) on train ridership was influenced by land use characteristics of catchment stations. The causality of effective density on ridership was compared between station groups. Findings showed the effect of treatment group was higher in the matched sample compare to the unmatched sample. This difference may be assigned as the true effect of public transport induced agglomeration which was higher after controlling the land use characteristics of stations. Thus, the inclusion of land use variables in the model prediction may has the effect of rendering the influence of effective density variable lower in the model. These findings could guide station catchment area planning to maximise effective density benefits on train ridership.

Accessibility represents a paramount metric for assessing the service level of public transportation systems. Current research predominantly focuses on urban intra-system accessibility, with limited holistic studies encompassing small-to-medium-sized cities, adjacent towns, and rural areas. Traditional metrics like bus mode share, route length, and road density inadequately quantify urban-rural transportation supply. Existing methods rely on travel distance and assumed bus speeds, neglecting actual time-based assessments. Building upon the gravity model, this study proposes a regional bus accessibility model, using real travel time as impedance and supply-demand ratio as a weighting factor, and visualizes results through ArcGIS spatial analysis. Leveraging Python scraping technology and the Gaode Map Open Platform, we obtain actual bus travel durations between origins and destinations. Taking 16 traffic zones in Tengzhou County as examples, we analyze temporal-spatial differences in bus travel between urban and rural-village zones. The accessibility results intuitively reveal the level of bus accessibility from urban centers to surrounding villages, providing quantitative information crucial for site selection analysis and public transport optimization.

In recent years, the rapid expansion of urban rail transit has significantly improved travel efficiency, yet it has also exacerbated spatial inequality in service coverage. Accessibility, as a fundamental metric for evaluating the equity of service distribution, remains limited by three major shortcomings in current assessment methods: the neglect of actual road network characteristics, reliance on a single static scale, and the absence of quantitative mechanisms to assess accessibility equity. These deficiencies hinder a comprehensive understanding of how equity evolves with the spatiotemporal dynamics of rail systems. To address the aforementioned issues, this study proposes an innovative spatiotemporally dynamic and multi-scale analytical framework for evaluating urban rail accessibility and its equity implications. Specifically, we develop a network-based buffer decay model to refine service population estimation by incorporating realistic walking paths, capturing both distance decay and road network constraints. The framework integrates multiple spatial analytical techniques, including the Gini coefficient, Lorenz curve, global and local spatial autocorrelation, center-of-gravity shift, and standard deviation ellipse, to quantitatively assess the equity and evolutionary patterns of accessibility across multiple spatial scales. Taking the central urban area of Hangzhou as a case study, this research investigates the spatiotemporal patterns and equity changes in metro station accessibility in 2019 and 2023. The results indicate that the expansion of the metro network has partially improved overall accessibility equity: the Gini coefficient at the TAZ (Traffic Analysis Zone) scale decreased from 0.56 to 0.425. Nevertheless, significant inequality remains at finer spatial resolutions (grid-level Gini coefficient = 0.404). In terms of spatial pattern, the core area (e.g., Wulin Square) forms a ‘high-high’ accessibility agglomeration area, while the urban fringe area (e.g., northern Yuhang) presents a ‘low-low’ agglomeration, and the problem of local ‘accessibility depression’ still exists. Additionally, the accessibility centroid has consistently shifted northwestward, and the long axis of the standard deviation ellipse has rotated from an east–west to a northwest-southeast orientation, indicating a growing spatial polarization between core and peripheral zones. The findings suggest that improving equity in urban rail accessibility cannot rely solely on expanding network size; rather, it requires coordinated strategies involving network structure optimization, branch line development, multimodal integration, and the construction of efficient transfer systems to promote more balanced and equitable spatial distribution of rail transit resources citywide.

Urban park green spaces (UPGSs) play a critical role in enhancing residents’ quality of life, particularly for older adults. However, inequities in accessibility and resource distribution remain persistent challenges in aging urban areas. To address this issue, this study takes Gulou District, Nanjing City, as an example and proposes a comprehensive framework to evaluate the overall quality of UPGSs. Furthermore, an enhanced Gaussian two-step floating catchment area (2SFCA) method is introduced that incorporates (1) a multidimensional park quality score derived from an objective evaluation system encompassing ecological conditions, service quality, age-friendly facilities, and basic infrastructure; and (2) a Gaussian distance decay function calibrated to reflect the walking and public transit mobility patterns of the older adults in the study area. The improved method calculates the accessibility values of UPGSs for older adults living in residential communities under the walking and public transportation scenarios. Finally, factors influencing the social equity of UPGSs are analyzed using Pearson correlation coefficients. The experimental results demonstrate that (1) high-accessibility service areas exhibit clustered distributions, with significant differences in accessibility levels across the transportation modes and clear spatial gradient disparities. Specifically, traditional residential neighborhoods often present accessibility blind spots under the walking scenario, accounting for 50.8%, which leads to insufficient accessibility to public green spaces. (2) Structural imbalance and inequities in public service provision have resulted in barriers to UPGS utilization for older adults in certain communities. On this basis, targeted improvement strategies based on accessibility characteristics under different transportation modes are proposed, including the establishment of multi-tiered networked UPGSs and the upgrading of slow-moving transportation infrastructure. The research findings can enhance service efficiency through evidence-based spatial resource reallocation, offering actionable insights for optimizing the spatial layout of UPGSs and advancing the equitable distribution of public services in urban core areas.

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This article examines seniors’ accessibility to health care. The aim of the study was to analyse accessibility by public transport to primary health care facilities in the context of the services of general interest (SGI) concept. Four rural municipalities (with different functions) in the Podkarpackie Voivodeship were selected as the study area: Jawornik Polski, Horyniec-Zdrój, Komańcza and Gorzyce. In the first step, the demographic situation in the municipalities was described. Next, the distribution of public transportation stops in each municipality and the timetables of the carriers operating there were analysed. The highest accessibility to bus stops, measured by distance, was found in the municipalities of Komańcza and Gorzyce. On the other hand, the municipalities of Gorzyce and Jawornik Polski had the highest number of public transport services to primary healthcare facilities. Low accessibility in the municipality of Horyniec-Zdrój indicated that the provision of services of general interest may be insufficient in peripheral rural areas.

This study aims to analyze the effectiveness of the integration of the Bus Rapid Transit (BRT) system with feeder transportation in improving the connectivity and accessibility of public transportation in Medan City. The research methods used include field surveys, interviews, and spatial analysis based on Geographic Information Systems (GIS) to map the transportation network and assess the scope of services. The analysis was carried out by comparing the existing conditions of the BRT (Corridors 2 and 3) and the results of the simulation after the integration of five feeder routes (A2, A3, A6, A7, and A8). The results show that the integration of feeder routes is able to increase service coverage from 57.84 km² to 128.84 km² (an increase of 122.8%), as well as expand the served area from 23 to 44 zones, with an increase in service ratio from 26% to 57%. In addition, the average distance to the bus stop decreased from 1.2 km to 0.6 km, and the route overlap was reduced by 40%. Spatially, areas with high accessibility (<500 m from bus stops) have increased significantly in city centers such as Merdeka Square and Petisah Market. This study concludes that the integration of BRT and feeder is an effective strategy to realize a sustainable, efficient, and inclusive transportation system in the city of Medan. The implementation of a rotating operating system is also recommended to optimize the fleet without the need for the addition of new vehicles.

In land transportation, the terminal is part of the transportation service network as a node of a series of land transportation networks in each city. High travel rates by public vehicles such as buses that are not matched by good traffic arrangements will cause problems such as congestion. The study was conducted to determine the pattern of travel movements (Trip Distribution) of bus passengers in several regions in East Java in an Origin-Destination Matrix (MAT) using the Synthetic Method, namely the Unsconstrained Gravity Model. Alternative methods for calibrating parameters in the gravity model are α and β, which are parameters of the barrier function (accessibility) between zones . The approach used in this research is a quantitative descriptive approach using the Google Earth application media to measure the distance between one city and another. The results obtained Alpha (α) value of 5.82 and the best R Square of 0.0917 with y = 13.682x for MAT Power and Beta (β) value of 0.0098 and the best R Square value of 0.0635 with y = 1E - 10x.  The distribution modeling formula for East Java zone bus passengers .  

This study aimed to analyze the characteristics and influencing factors of the access trips of railway users in the Seoul Metropolitan Area, South Korea. A total of 11 metropolitan railway stations and 4 urban railway stations were selected, and data on users’ travel characteristics—including access modes, travel purposes, demographic attributes, and whether they were accompanied by infants—were collected through one-on-one interviews. Based on 1683 collected cases, the data were analyzed using a multivariate analysis of variance (MANOVA). The results showed a statistically significant difference between bus access distances, which were 1.78 km for metropolitan railways and 1.59 km for urban railways. In contrast, the walking access distances were approximately 620 m for both, showing a minimal difference. The further analysis of factors influencing the access distance revealed that apartment ownership, users’ income level, the presence of accompanying travelers, the distance between stations, the number of transfer routes, and whether users were traveling with infants had significant effects.

The multi-modal two-step floating catchment area (MM-2SFCA) method is an extension of the two-step floating catchment area (2SFCA) method that incorporates the impact of different transportation modes, thereby facilitating more accurate calculations of the spatial accessibility of public facilities in urban areas. However, the MM-2SFCA method does not account for the impact of distance within the search radius on supply–demand capacities, and it assumes an idealized supply–demand relationship. This paper introduces the gravity model into the MM-2SFCA method, proposing a multi-modal gravity-based 2SFCA (MM-G2SFCA) method to better account for distance decay and supply–demand relationships. Furthermore, a standardized gravity model is proposed based on the traditional gravity model. This model imposes constraints on upper and lower limits for distance decay weights without compromising the fundamental curve characteristics of the gravity model, thereby avoiding extreme weight scenarios. The accessibility of public hospitals in Shenzhen is evaluated through the integration of basic geographic information data, resident travel data, and official statistical data. The findings demonstrate that the standardized gravity model effectively addresses the issue of excessively high local distance weights in the traditional gravity model, making it more suitable as a distance decay function. The MM-G2SFCA method improves the consideration of distance and supply–demand relationships, thereby facilitating a more rational distribution of accessibility on a global scale. This study discovers differences in the spatial allocation of public hospital resources across the Shenzhen’s districts. Accessibility within the metropolitan core is significantly higher than that outside the core. Additionally, there is a notable difference in the level of accessibility among the districts. Accessibility is found to be better in district centers and along the main traffic arteries.

Public transport improves mobility and well-being for the rapidly aging population. However, few planning interventions have addressed the urban–rural disparity in bus usage among older adults. Using data from Zhongshan, China, this study adopts the eXtreme Gradient Boosting (XGBoost) model to examine urban–rural differences in the nonlinear relationship between built environment and daily bus usage among elderly adults. The results indicate nonlinearities across all built environment variables and stronger effects of the built environment in rural areas. Distance to transit contributes the most in urban neighborhoods but least in rural ones. Furthermore, dwelling unit density and green space accessibility play the biggest roles in the rural context. Additionally, the most effective ranges of intersection density, land use mixture, and CBD accessibility are greater in rural areas. The findings facilitate fine-grained and diversified planning interventions to facilitate bus usage among older adults in both urban and rural areas.

Spatial accessibility to healthcare services is a key determinant of health equity, especially among aging immigrant populations. This study examines disparities in access to preventive healthcare services between older Korean immigrants and nonimmigrant older adults in Los Angeles, USA. Using the generalized two‐step floating catchment area (G2SFCA) method, we assess spatial accessibility by considering supply–demand dynamics, travel behavior, and distance‐decay effects, which capture the decreasing likelihood of healthcare utilization as travel distance or time increases. The findings indicate that older Korean immigrants experience lower levels of accessibility to preventive healthcare services compared to nonimmigrant older adults, including longer travel distances and more limited availability of linguistically and culturally appropriate services. While nonimmigrant older adults generally have better access, older Korean immigrants often need to travel further to find care that meets their linguistic needs. These disparities highlight the role of geographic, linguistic, and structural barriers in shaping healthcare accessibility. To address these challenges, policy interventions such as increasing Korean‐speaking healthcare providers, expanding mobile healthcare services, and improving transportation options are necessary. This study contributes to the discourse on healthcare equity and immigrant health, emphasizing the need for targeted strategies to improve access to preventive care for aging immigrant populations. By addressing gaps in existing accessibility measures for immigrant populations, this study opens avenues for future research that integrates individual‐level constraints and qualitative approaches.

The Yangtze River Delta (YRD) region is one of the areas in China with the highest level of transportation integration, featuring a well-developed high-speed rail network, multimodal transport system, interconnected intercity bus services, and intelligent transportation platforms. These developments have brought about significant effects of time-space compression in the region. Under the effects of time-space compression, the changes in the regional socio-economic spatial structure are worth further exploration. To this end, from the perspective of accessibility, this study explores the time–space compression effect in the YRD region using models such as economic linkage strength (ELS), central city isochronous-ring, daily accessibility (DA), and employment accessibility (EA) indicators. The results show: (1) The time distance between central cities and prefectural-level and lower-tier cities has greatly decreased, resulting in a network-based structure and a trend towards urban system flattening; within 1–2 hours of central cities, the scale of the population, number of cities, and regional coverage area have rapidly expanded, promoting regional integration and urban agglomeration. (2) Intercity time-space compression has significantly increased the total ELS between cities, intensifying the “strong center” economic linkage pattern. The radiation and driving capacity of central cities for the region has notably increased, and the equilibrium of urban economic linkage capabilities has improved. (3) Time-space compression strengthens the “competitive-cooperative effect” of central cities, facilitating the convenient sharing and equalization of high-quality urban public services, but also leading to tensions in the supply and demand of these resources. (4) A high-accessibility region has formed in the “Shanghai-Nanjing-Hangzhou” triangle, where high-accessibility cities possess larger market hinterlands and more employment opportunities, providing significant opportunities for the rise of small and medium-sized cities in peripheral areas. Based on these findings, in the context of time-space compression, these regions should actively build convenient, efficient, and resilient commuting and transfer networks. A networked spatial development strategy should be implemented, establishing efficient regional collaboration mechanisms and public service cooperation systems to promote coordinated regional development.

The lack of optimal bus routes has been a great problem for the effective operation of the transport system in the Federal Capital City. This has resulted to challenges, such as, inadequate accessibility to public buses, long time of walking to or waiting at bus stops as faced daily by commuters.The results of the assessment of the current bus route network in the Federal Capital city suggested that there is need to optimize the present bus route networks to connect with all the districts of the City for overall accessibility to commuters. This study therefore  determines the optimum bus route network for the City using Ant Colony Optimization Technique. Geographic Information Systems (GIS) were utilized to determine more efficient passenger routes based on the insights derived from the trip distribution analysis. Consider factors  such as travel time, travel distance, traffic congestion, and transportation mode preferences to develop passenger routes that are both time-efficient and cost-effective. A combination of an interview, a questionnaire and a GPS (Garmin76x) was used to gather information from commuters and public transportation operators  to determine trip production and attraction of districts; travel time and travel distance from districts to districts. Geographic Information System (GIS) in Arc-GIS 10.6.1 environment, was employed to analyze and modify the gathered data to digitize the map of the City showing  districts, road network and trip distribution of  residents. The study revealed that the current bus routes network does not cover the routes that have concentration points of movement of commuters; therefore, compared to public buses, which have fares ranging from ₦50 to ₦100 every drop, passengers who use registered taxis and unofficial private automobile taxis spend excessive amounts of money on transportation fees. These taxis' fares range from ₦200 (400%) to ₦500 (500%) per drop. The optimized and optimum bus routes network provided in this study are suggested for implementation  to facilitate an effective bus service operating system in the Federal Capital City.

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With the ongoing spread of COVID-19, vaccination stands as an effective measure to control and mitigate the impact of the disease. However, due to the unequal distribution of COVID-19 vaccination sites, people can have different levels of spatial accessibility to COVID-19 vaccination. This study adopts an improved gravity-based model to measure the racial/ethnic inequity in transit-based spatial accessibility to COVID-19 vaccination sites in the Chicago Metropolitan Area. The results show that Black-majority and Hispanic-majority neighborhoods have significantly lower transit-based spatial accessibility to COVID-19 vaccination sites compared to White-majority neighborhoods. This research concludes that minority-dominated inner-city neighborhoods, despite better public transit coverage, are still disadvantaged in terms of transit-based spatial accessibility to COVID-19 vaccination sites. This is probably due to their higher population densities, which increase the competition for the limited supply of COVID-19 vaccination sites within each catchment area.

This paper proposes a spatial difference analysis method for evaluating transit-based accessibility to hospitals using spatially adjusted ANOVA. This method specializes in examining spatial variations of accessibility to hospitals by regions (i.e. administrative districts or subdistricts). The spatial lag model is applied to adjust traditional ANOVA, which reduces spatial dependency and avoids false rejection to null hypothesis. Multiple comparison methods are used for further detection of differences in accessibility between regions. After multiple comparison, accessibility within regions is classified into three levels. The study is conducted on two scales—administrative districts and subdistricts—to discuss spatial variations in macro and micro dimensions respectively in the central part of Wuhan, China. Accessibility is calculated by using a simple model and a gravity model. The final classification results showed that the spatially adjusted method is more reliable than the traditional non spatially adjusted one and the gravity model can better detect more hidden information about the inequal distribution of medical resources. It is also found that the subdistricts, which have significantly lower accessibility to hospitals than others, are mainly distributed in Hongshan and Qingshan district. Our study hopes to shed new lights in spatial difference analysis for accessibility and provide policy recommendations that would promote equality in provisions of public health services.

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The shortest path model is selected to evaluate the regional traffic accessibility. Three index factors, gross regional product, total retail sales of consumer goods, and the number of permanent residents in the region, were selected, and the weight sum was given by entropy weight method to evaluate the regional economic intensity. The gravity model adding the regional accessibility index considering traffic factors is selected to evaluate the regional linkages. By integrating the three indexes, an evaluation index system of rail transit benefits is formed to study the utility of rail transit to the economic development of surrounding areas, and to provide scientific theoretical basis and guidance for the government to carry out urban construction and rail transit management.

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Abstract. Transit accessibility plays a pivotal role in shaping mobility equity and urban sustainability, particularly in rapidly developing suburban environments where formal public transport infrastructure is often fragmented. This study presents a novel GIS-based Transit Accessibility Index (TAI) model integrating Fuzzy Analytic Hierarchy Process (FAHP) with Weighted Overlay Analysis (WOA) to assess transit service equity in Puncak Alam, Malaysia. Nine spatial criteria namely job density, land use, travel time, frequency, reliability, and demographic vulnerability were evaluated using expert-derived fuzzy weights and reclassified into a common scale using Jenks natural breaks. A consistency ratio check (CR = 0.088) validated the reliability of the expert judgment matrix. Site verification confirmed that high TAI zones, such as Alam Suria and Sungai Buloh, correspond with dense transit infrastructure, while low-accessibility areas exhibited limited-service coverage and unfavourable demographic or land use profiles. A sensitivity analysis adjusting the weight of the “age” criterion demonstrated the model’s robustness, with minimal impact on spatial outcomes. The study offers a reproducible, adaptable framework for transit equity assessment in suburban contexts and informs data-driven planning for future Transit-Oriented Development (TOD) and last-mile service optimization. Findings support the integration of FAHP-GIS models in accessibility planning and contribute to the advancement of spatial equity methodologies in emerging urban peripheries.

Although the transportation accessibility benefits afforded by multiple transportation modes play a fundamental role in determining transportation costs and land prices, there are challenges associated with isolating how multimodal accessibility benefits are capitalized into property values. In response, this research extends calibrated gravity-based measures of potential accessibility to employment by car and transit to include mode share proportions for commuting to reflect how this accessibility potential is realized. These realized accessibility measures capture not only the presence but also the performance of different modes for facilitating commuting trips. Spatial econometric models examine the extent to which access is capitalized into property values across Canada’s twelve largest metropolitan regions. Results suggest that car and transit access potential is generally valued across most cities, although there is evidence of moderate multicollinearity between the unweighted car and transit access potential scores. In contrast, the origin and destination mode use weighted measures of realized access offer advantages in terms of model performance and interpretation. These models show that premiums are generally linked with trade-offs between car and transit access, with the highest overall premiums found for properties in locations with the highest levels of transit access and transit use for commuting in most cities.

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Many older adults face the prospect of driving cessation as they age. Ensuring that public transit services meet their needs could contribute to their independent mobility and long-term health. Accessibility, the ease of reaching destinations by a certain mode, is a measure that can be used to indicate how well the land use and transport systems allow people to reach their desired destinations. This paper explores how perceived and objective levels of accessibility influence older adults ’ frequency of public transit use in a Canadian context. Based on a survey collected in six Canadian regions (N = 2,452), we use respondents ’ stated reasonable travel time by public transit to generate a personal-time-based cumulative accessibility measure. We then develop a weighted binary logistic regression model to understand the impacts of the personal-time-based accessibility measure, perceived accessibility, and other personal characteristics on older adults ’ frequency of public transit use. The results indicate that both perceived and personal-time-based accessibility have a strong and positive impact on frequent public transit use. Older women were found to be more frequent public transit users, whereas older adults who have access to a private vehicle use public transit significantly less. Findings from this research support the utilization of accessibility by public transit as a tool to better assess and plan for the transport needs of older adults. The results can be relevant for transport planners and policy makers interested in improving the well-being and independence of older adults through increasing their use of public transit.

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This study develops a spatial transit accessibility assessment method within a multicriteria decision-making framework. The method adopts the analytic network process to account for interdependence between criteria and across neighborhoods, and is applied to a case study in the Taipei metropolitan area in Taiwan. The assessment incorporates nine criteria across three perspectives: access to transit (population coverage of rail, bus, and public bike systems), service quality (frequency of rail and bus services and the number of public bike docks), and access by transit (opportunities to reach jobs, schools, and neighborhoods within a sixty-minute travel time). Criteria data were obtained from governmental open data platforms, official statistics, and Google Maps route planning, with 2021 as the base year. Expert surveys were conducted to determine the relative importance and interdependence of criteria. Spatial regression models and sensitivity analyses are conducted to evaluate how effectively the proposed accessibility measure explains variations in neighborhood-level transit mode share and to assess the robustness of the results. Results reveal significant spatial clustering of transit accessibility, confirming the influence of interdependence across neighborhoods. Moreover, the proposed method yields assessment results with greater explanatory power than those derived from single-criterion or independence-assuming approaches. These findings underscore the method’s utility for local authorities in identifying transport-disadvantaged neighborhoods and developing targeted accessibility improvement plans.

Abstract Efficient urban facility access is crucial for enhancing residents’ well-being and quality of life. This study examines public transport accessibility to essential facilities in Rome, such as high schools and hospitals, using gravity models based on open data sources, like OpenStreetMap and GTFS. Two versions of the gravity model are compared: an origin constrained and a doubly constrained. The latter can consider the capacity of facilities as a strict constraint, offering thus a more realistic assessment of accessibility. The findings highlight the correlation of public transport quality and urban accessibility, showing how variations in public transport supply affect the weighted average time to reach services like healthcare, education, and leisure. This approach reveals specific zones needing improvement and provides a valuable tool for predicting the impact of future changes in the transport network with respect to social equity. An online platform has been developed to allow a readily available application of this methodology to boost active citizenship and proactive decision making.

This study examines the differences in service level and coverage of public transit (PT) and private vehicles (PV) with multi-source data in Shanghai. To construct computable networks and address visual results, the constrained shortest path algorithm and a spatial grid accessibility model are employed to seek the optimal path for travelers to city key points. Travel time ratio of PV and PT is applied to reflect the competitiveness of the two modes over different areas of Shanghai. Results show that for PV, although the average travel time meets the needs of car travel, 51 % of the population cannot get to graded city centers within 45 min. In addition, the PV accessibility gradually weakens from the central city to the outside, highways and expressways may be feasible solutions. For PT, half of the population can't reach any city key points within two transfers, and almost all of these people live in the suburbs. Less than 30 % of the population can reach the city key points within 1 h, of which rail transit contributes more than conventional buses. Furthermore, the travel accessibility of PV is much better than that of PT. The average travel time ratio in all comparable grids is 2.04 for hubs, and 2.10 for graded city centers. For travels to graded city centers, the travel time ratio of suburbs is 35 % higher than that of central city, indicating that the inequity distribution of public transportation resources is worse in the suburbs than in the central city. This study also measures equity performance of groups based on spatial location and income level, and we find out that more core locations and higher income lead to higher accessibility. The gap among groups is significant, with a Gini coefficient over 0.5.

As the main form of new urbanization, the coordinated development of cities in metropolitan areas requires reliable and efficient rail transit skeleton support. However, in the rapid development of metropolitan areas, the layout and analysis of multi-level rail transit systems have a certain lag. Taking the Xi’an metropolitan area as an example, this study analyzes the comprehensive accessibility and resilience of the multi-level rail transit network, and proposes an expansion plan accordingly. The traffic analysis zone (TAZ) is divided by towns and streets, and the relationship between points of interest (POIs) and the regional average level is analyzed using DEA. The improved weighted average travel time model is built with the analysis results as regional weights; a site selection model based on multiple construction influencing factors is proposed, and four expansion plans, namely, economic optimal, environmental optimal, transport optimal, and integrated optimal, are designed. The peak passenger flow scenario and the “failure–reparation” scenario during the entire operation period are designed to analyze the resilience of four plans, and the resilience is quantified by the elasticity curve of the maximum connected subgraph ratio (MCSR) changing over time. The research results show that the transport optimal plan has the best comprehensive accessibility and resilience, reducing travel costs in Houzhenzi Town, which has the worst accessibility, by 34%. The expansion model and evaluation method in this study can provide an empirical example for the development of other metropolitan areas and provide a reasonable benchmark and guidance for the development of multi-level rail transit networks in future urban areas.

Post-secondary students are a segment of the population whose activity-travel behaviour is not well understood. In particular, there is a relative dearth of studies that have examined the determinants of behaviours related to participation in out-of-home activities among post-secondary students. This study uses data from a web-based survey administered to students attending universities in Toronto to examine the determinants of the location choice decisions of these individuals when using transit to participate in non-mandatory activities. Additionally, count- and utility-based measures of accessibility by transit for university students in Toronto are calculated and compared. The specification of the location choice model offers insights into the determinants of location choice decisions made by university students for non-mandatory trips. The results highlight the impacts of transit level-of-service and land use attributes on location choice decisions. Moreover, the findings suggest that the impacts of these attributes can differ based on socio-demographic characteristics. The comparison of count- and utility-based accessibility measures underscores the shortcomings of the former, which stem from the treatment of all opportunities as equally attractive. The results of this study aim to contribute to the literature by offering insights into an aspect of the activity-travel behaviour of post-secondary students that has received relatively little attention. Similarly, the results of the study can be used to help inform planning decisions by shedding light on the activity-travel behaviour of a segment of the population that has typically been underrepresented in traditional household travel surveys.

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The accessibility of public transport is a vital factor for the overall success of transit operations. It determines whether people choose to use and rely on public transport by assessing the ease of accessing opportunities. Accessibility, as a measure of the system’s performance, encompasses various travel segments and can be evaluated from different perspectives. Evaluating transit accessibility in data-constrained environments, particularly in developing countries, requires an optimal framework. The present study proposed a framework by modifying available accessibility measurement indices and trying to encompass all affecting variables in a single composite index. The integrated transit system comprising the bus rapid transit system and city bus in Surat city, India, is selected to demonstrate the proposed framework. The results of the ranked-based correlation coefficient test exhibit the comprehensive assessment capabilities of the proposed composite index in evaluating transit performance. Surat city’s transit network shows better coverage based on the gravity model theory, that is, moderate performance in local coverage offered capacity per population. However, it exhibits poor accessibility with respect to reaching destinations, resulting in below-average transit accessibility. Except for the city center and eastern part, 65% of the city area experiences inadequate accessibility of public transport. These findings align with the city’s low transit mode share of 2.5% and stagnant daily ridership of 0.25–0.28 million passengers in the last half decade. The composite index map serves as a planning tool for optimizing the utilization of available resources and guiding future policy implementations.

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Accessibility to a fixed point of interest is a powerful indicator for quantifying the strengths and weaknesses of a multimodal pedestrian and transit network. However, it is difficult to predict the impact on accessibility deriving from the insertion of a new infrastructure and its contribution to the urban landscape. This paper uses graph science and multisource open data to implement a tool for studying accessibility in combination with several network performance indicators. The tool allows determination of whether a transit infrastructure project can be beneficial for its potential users. In this paper, we propose to compute gravity-based accessibility, temporally bounded by an isochrone T . We assume that the user always favors the shortest route, her rationality conditioned by real-time applications provided by network operators. By the proposed approach, the impacts on accessibility deriving from the construction of a new infrastructure, such as a new transit line, can be effectively quantified and the actors of urban planning can visually evaluate the consequences of their projects to make more informed decisions.

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The rational layout of prefecture city rail transit network is of great significance to the coordinated development of urban and rural areas. This paper analyses five related factors that affect the layout of rail transit and grey relation analysis is used to analyse the correlation degree and weight of five related factors. Based on this, an improved gravity model describing the attraction between towns is built. The improved gravity model is used as the road weight, and the urban rail transit network layout is obtained by graph theory Kruskal algorithm. Finally, taking the urban rail transit network in Handan as an example, the rationality and feasibility of the model and layout method are checked.

Urban sustainability depends on balancing transportation accessibility, housing affordability, and social equity. Displacement—defined in this study as the population-level loss of low-income households from a census block over time—poses a growing challenge to inclusive urban development. This study examines statistical relationships and spatial patterns linking transit accessibility, housing affordability, and low-income household displacement across the four largest counties in Tennessee. Negative binomial regression models are used to quantify relationships between transit accessibility, housing affordability, and displacement, revealing that housing affordability is consistently linked to displacement, while the effects of transit accessibility vary substantially across counties. Bivariate Local Indicators of Spatial Association (LISA) identify localized clusters where displacement coincides with transit or housing constraints, and Multivariate Cluster Typology Analysis classifies census blocks into distinct typologies, highlighting region-specific trade-offs between accessibility and affordability. Together, the results demonstrate that displacement dynamics are highly context dependent, underscoring the need for place-based and sustainability-oriented policy responses. The findings provide an empirical basis for integrating transportation and housing strategies to reduce displacement risks and support equitable and sustainable urban development in diverse metropolitan contexts.

ABSTRACT Most of the current existing accessibility measures quantify the potential of reaching desirable opportunities across space and time. Nevertheless, these potential measurements only illustrate the maximum possible accessibility a person can have, which may not accurately measure real-world transit accessibility in urban areas. This paper introduces a novel methodology to measure positive public transit accessibility based on multi-source big public transit data such as Smart Card Data (SCD) and Global Navigation Satellite System trajectory data, which embed rich travel information and real-world spatio-temporal constraints. First, we use multi-source transit data to reconstruct trip chains, which are used to extract popular destinations. A novel transit accessibility measure is defined to account for latent trip information such as mode/route preference, opportunity attraction, and travel impedance that are difficult to capture explicitly via traditional normative measures. Finally, we produce accessibility maps to visualize time-varying and heterogeneous accessibility patterns distributed over the study region. We performed an empirical evaluation on real-world transit data collected in Shenzhen City, China, demonstrating the applicability and effectiveness of the proposed method in mapping positive transit accessibility over large metropolitan areas. The results and findings of the empirical study demonstrate that the proposed positive accessibility measure can better capture travel behavior characteristics and constraints than traditional normative measures. The measurement method can be used as a practical high-resolution mapping tool for transit decision makers in evaluating public transit systems, supporting strategic transit planning, and improving daily transit management.

Transit accessibility is an explanatory variable evaluating the mobility of a region in consideration of the connectivity and demand among the regions, which has been used for an important index to determine transport policy on the transit network. This study aims to develop an accessibility index considering the two factors with a demand-weighted approach, that is, impedance and attraction level. Two variables, travel time and the ratio of trips, are employed to calculate the accessibility index, and comparative assessments between zones are conducted. The application of smart card data makes it possible to analyze travel information and reflect them empirically in the model. This study identifies zones with vulnerable accessibility and suggests criteria for transit investment plans with two aspects, that is, intensive transit area and spatial distribution of the accessibility index. These aspects contribute to transit planners by suggesting transit investment criteria and comprehensible statistics to evaluate accessibility. Since zones with low accessibility indexes are identified as being vulnerable to access from other zones, policymakers should focus on those zones to improve the overall transit network.

Abstract. As dynamic accessibility depends on the interplay of opportunities and travel impedance, available General Transit Feed Specification data and mobile phone data offer new opportunities to enhance the temporal sensitivity of accessibility. This paper utilises a mobile phone-based origin-destination matrix and dynamic travel time via public transport to explore spatial and temporal patterns of accessibility measures. Four scenarios are constructed and compared to illustrate the relative accessibility. The results show that the impact of the public transport system changes progressively depending on the cut-off time considered, and average accessibility gains could vary four-fold between the city centre and suburban zones. Besides, the exploration of the relationship between land use, mobile phone-based attractiveness, and dynamic accessibility underlines the time-dependent effect of land use. Future research should focus on the development of advanced accessibility-based travel models.

Reviewing the existing equity of accessibility approaches, particularly the transit models, revealed that these methods tend to consider the actual economic condition of individual or group living in various areas, real transport network and travelers traveling patterns (especially during peak traffic periods). Existing transit accessibility approaches have typically proposed simple time-based measurements to explain the transit network accessibility under hypothetical road conditions and accessibility to transit corridors (transit stops). These studies overlooked to estimate transit accessibility. As a result, these approaches failed to describe the actual impedance of the transit network. These simple methods tend to capture the objective of accessibility. The aim of this research is to analyses urban accessibility considering its two components the performance of the transport network and the attractiveness of the destinations using a more dynamic approach. This will allow us to obtain profiles that highlight the daily variations in accessibility in the study area, and identify the influence of congestion and the changes in location choice behavior. Accessibility conditions change throughout the day, as do the causes of these changes, namely congestion in the road network and the population distribution in the city. Each transport zone has its own accessibility profile, and thus its own specific problems, which require solutions that are more specific. The dynamic approach proposed in this paper involves calculating the accessibility of each transport zone. This will allow a dynamic approach to population distribution in the city.

Spatial accessibility to general hospitals is an important indicator of the convenience and ability of residents to obtain medical services. Therefore, developing a model for measuring accessibility to general hospitals by multiple transportation modes is necessary. In this study, considering that the increase in travel time will reduce the attractiveness of general hospitals, we used the Two-Step Floating Catchment Area with the Gaussian attenuation function, in which the supply was presented by capacity of hospitals (i.e., number of beds), and the demand was presented by population in each grid derived with social media data mapping real-time locations of active users. The Gaussian Two-Step Floating Catchment Area (Ga2SFCA) simulates the attenuation tendency of the general hospital service capabilities over transit time. To obtain a highly precise understanding of accessibility to hospitals, transit time on Baidu Maps’ navigation service was used as the impedance condition, and the study area was divided into 1 square kilometer grids as the basic unit of research. Taking Nanjing city as a case study, it is found that the accessibility distribution shape changes from a multi-centered circular pattern to a multi-peak distribution, as the time threshold increases. By comparing the accessibility among 11 districts varying from main urban area to suburbs, the accessibility to general hospitals in Nanjing is significantly regionally unbalanced in both travel modes. By calculating and mapping the Modal Accessibility Gap (MAG) of the two travel modes, different modes of transportation resulted in different general hospital accessibility distributions. Generally, private car is superior in access to general hospitals to public transit in most areas. In the central area, public traffic may not contribute to the access to medical services as much as we thought, rather it plays a role in areas far from hospitals along metro lines and bus routes.

Two-step floating catchment area (2SFCA) methods that account for multiple transportation modes provide more realistic accessibility representation than single-mode methods. However, the use of the impedance coefficient in an impedance function (e.g., Gaussian function) introduces uncertainty to 2SFCA results. This paper proposes an enhancement to the multi-modal 2SFCA methods through incorporating the concept of a spatial access ratio (SPAR) for spatial access measurement. SPAR is the ratio of a given place’s access score to the mean of all access scores in the study area. An empirical study on spatial access to primary care physicians (PCPs) in the city of Albuquerque, NM, USA was conducted to evaluate the effectiveness of SPAR in addressing uncertainty introduced by the choice of the impedance coefficient in the classic Gaussian impedance function. We used ESRI StreetMap Premium and General Transit Specification Feed (GTFS) data to calculate the travel time to PCPs by car and bus. We first generated two spatial access scores—using different catchment sizes for car and bus, respectively—for each demanding population location: an accessibility score for car drivers and an accessibility score for bus riders. We then computed three corresponding spatial access ratios of the above scores for each population location. Sensitivity analysis results suggest that the spatial access scores vary significantly when using different impedance coefficients (p < 0.05); while SPAR remains stable (p = 1). Results from this paper suggest that a spatial access ratio can significantly reduce impedance coefficient-related uncertainties in multi-modal 2SFCA methods.

With reference to the hospitalizing trips made by the elderly, the impedance of these trips that require the use of public transportation, is introduced. An evaluation model that can accurately detect the accessibility of high order urban hospitals (HOUHs) for the elderly is established with the help of Geographic Information System (GIS) technology. Furthermore, the established model is employed to detect the accessibility of first-level hospitals in Xi’an City. Results showed that the traffic connection between hospitals and their service objects is an important factor for the feasibility and effectiveness of an accessibility evaluation. It is suggested that special evaluations of the accessibility of hospitals for the elderly are needed to achieve the human-oriented goal of urban traffic planning. The well-served spatial pattern of hospitalizing accessibility for the elderly in Xi’an City has been established in recent years because of the strategies for public transit metropolis. The accessibility constraints can be divided into three types: The imprisonment, the antagonism and the running-in, for which the corresponding countermeasures to settle the low accessibility of hospitals will be taken by the planning administration. Attention is paid to specific population groups during their hospitalizing trips in the accessibility research, which is beneficial for enabling the improvement of the current traditional method which is mainly based on travel facilities.

In this paper a contribution is presented with respect to accessibility indicators modelling for commuters moving through the municipalities of Sardinia, in Italy. In this case, spatial complex network analysis is integrated into the construction of accessibility measures: one of the most relevant outcomes of the first tool –the detection of shortest road paths and distances- is adopted as an input for the second in modelling accessibility indicators. Instead of Euclidean distances often adopted in the literature, shortest road distances are chosen, as commuting implies movements that are usually repeated daily and very likely subjected, even unconsciously, to space and time minimization strategies. In particular, two commuter accessibility indicators are constructed according to approaches based on a travel cost and a spatial interaction model with impedance function calibrated in exponential and in power form. The accessibility indicators are confronted each other and with relevant socio-economic and infrastructure characteristics of Sardinia. In addition, they are described, with respect to their spatial distribution and their different implications, when adopted in decision-making and planning. The travel cost based accessibility indicator has a municipal spatial distribution strongly influenced by the main road infrastructure of the Island. By contrast, spatial interaction model based accessibility indicators are more reliable, with respect to their capacity to confirm a leading socio-economic role of the municipalities comprehended in the metropolitan area of the capital town Cagliari.

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