Journal of Transport Geography最新文献

{"title":"Heterogeneity in inter-episode intervals for discretionary activities; covariate-dependent finite mixture models","authors":"Pim Labee ,&nbsp;Seheon Kim ,&nbsp;Soora Rasouli","doi":"10.1016/j.jtrangeo.2025.104219","DOIUrl":"10.1016/j.jtrangeo.2025.104219","url":null,"abstract":"<div><div>Even though the importance of considering day-to-day variability in travel demand modeling has long been acknowledged in the field, most state-of-the-art activity-based models still only have a single-day prediction horizon. As such, bias arises from the aggregation to ‘an average’ day. A few which differentiate between days of the week (such as Albatross) still fail to incorporate dependencies between activities conducted in multiple days. Understanding the heterogeneity in (ir)regularity of discretionary activities and the inter-episode durations with which they are conducted, is a stepping stone to extend ABMs to multi-day horizon models. Over two years of GPS data from the Netherlands are used to estimate exponential models to capture irregular activity conductors, while Erlang-<em>k</em> models are estimated to represent the regular activity conductors. A mixture model of the exponential-Erlang-2 model is presented where the extent of activity-regularity is endogenously estimated. The heterogeneity within each group is estimated in a non-parametric fashion and, in certain cases, is shown to outperform the parametric equivalence. The proposed models are applied to grocery shopping, non-grocery shopping and leisure activities.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"126 ","pages":"Article 104219"},"PeriodicalIF":5.7,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An adapted centrality index to assess spatial accessibility in street networks: Application to two medium-sized cities in Brazil","authors":"Gustavo Maciel Gonçalves ,&nbsp;Clarice Maraschin ,&nbsp;Ana Luisa Maffini","doi":"10.1016/j.jtrangeo.2025.104238","DOIUrl":"10.1016/j.jtrangeo.2025.104238","url":null,"abstract":"<div><div>This paper explores an adapted network-based measure for assessing spatial accessibility in urban street networks: the Potential Accessibility (PA) index. Building upon network centrality measures and incorporating concepts from transportation and geography studies, the proposed index integrates spatial competition for limited-capacity opportunities into a directed, weighted network model. The PA index accounts for both supply (e.g., employment opportunities) and demand (e.g., population) attributes, and their spatial interaction within a global analysis or a local one (with a predefined catchment radius). To demonstrate the PA index's properties and practical relevance, we apply it to two medium-sized Brazilian cities, analyzing accessibility to formal employment opportunities. We conducted four experiments: an unweighted analysis, a supply-weighted analysis, a competition-based analysis with both supply and demand weights, and a local accessibility analysis using a 1600-m radius. A fifth experiment compares the PA index to Reach centrality, a non-competitive network-based accessibility measure. Results reveal how variations in street network configuration influence accessibility outcomes and inequality patterns, captured using the Palma Ratio. The PA index distinguishes local from global accessibility more effectively than the Reach index and better reveals how competition and proximity affect opportunity access. The method's flexibility allows for multiscalar analysis, integration of social attributes, and scenario simulations, supporting planning applications aimed at equitable access to services. The study contributes to accessibility research especially by introducing a network-based framework with the potential to enhance proximity-centered and local accessibility urban policies, particularly relevant to small and medium-sized cities.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"126 ","pages":"Article 104238"},"PeriodicalIF":5.7,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards vulnerability urban road networks: Adaptive topological optimization and network performance analysis","authors":"Yinghui Nie ,&nbsp;Jingpei Li ,&nbsp;Kum Fai Yuen ,&nbsp;Xin Mao","doi":"10.1016/j.jtrangeo.2025.104237","DOIUrl":"10.1016/j.jtrangeo.2025.104237","url":null,"abstract":"<div><div>To address the vulnerability of complex transportation networks during sudden events and attacks, this study focuses on the road network of Fucheng District in Mianyang City and proposes an adaptive topological expansion optimization model to enhance the original road network data. Densely populated region adjustments were considered to calculate the composite vulnerability index of nodes. The analysis examined road network composite vulnerability index changes under different intentional attack strategies (e.g., targeting nodes with the highest or lowest composite vulnerability index first) and user response behaviors (comprehensive information availability and limited information acquisition). The results indicate that targeting nodes with the highest vulnerability causes 2.5 times more overall vulnerability than targeting nodes with the lowest vulnerability. Under comprehensive information availability (CIA) conditions, the road network's composite vulnerability index decreases by approximately 0.02 compared to limited information availability (LIA) conditions. The adjustment method accounting for population density distribution effectively identifies and protects critical nodes, enhancing the composite importance index within densely populated regions. This research provides theoretical support and practical tools for improving the robustness and pre-disaster preparedness of transportation networks.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"126 ","pages":"Article 104237"},"PeriodicalIF":5.7,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cycling cities: Measuring urban mobility mixing in bikeshare networks","authors":"Timothy Fraser ,&nbsp;Katherine Van Woert ,&nbsp;Sophia Olivieri ,&nbsp;Jonathan Baron ,&nbsp;Katelyn Buckley ,&nbsp;Pamela Lalli","doi":"10.1016/j.jtrangeo.2025.104223","DOIUrl":"10.1016/j.jtrangeo.2025.104223","url":null,"abstract":"<div><div>To promote low-carbon transit, cities are increasingly adopting public-private partnerships to offer bikeshare services. But some neighborhoods use bikeshare services more than others, raising questions about how equitable these public programs' rollout has been. We examined the entire temporal directed network of individual rides from Boston's Bluebikes program, tracking bikers' starting and ending stations from 2011 to 2021. We hypothesized that ridership levels are lower between neighborhoods of color than white neighborhoods, and greater between wealthier neighborhoods than working class neighborhoods. We designed edgewise block permutation tests to measure the statistical significance of mobility between similar neighborhoods, while controlling through permutation blocks for population density, program geography, distance, and the distribution of race, wealth, education, and age. The network is deeply stratified by race and income, with more homophilous movement between neighborhoods from similar income brackets than expected due to chance. Race is linked to considerable homophily, but with low statistical significance. However, homophilous mobility by income and race has dropped sharply from 2011 to 2021, suggesting that Bluebikes is gradually reaching a broader range of neighborhoods. This presents signs of hope for a transition to equitable transit options in other major US cities as well.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"126 ","pages":"Article 104223"},"PeriodicalIF":5.7,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring factors influencing first-mile and last-mile connections to public transport from car users' perspective: Evidence from Greater Accra, Ghana","authors":"Eugene Sogbe ,&nbsp;Susilawati Susilawati ,&nbsp;Graham Currie ,&nbsp;Chee Pin Tan","doi":"10.1016/j.jtrangeo.2025.104240","DOIUrl":"10.1016/j.jtrangeo.2025.104240","url":null,"abstract":"<div><div>Public transport is commonly considered a solution to car dependence, aiming to address environmental degradation and social problems which car dependence creates in cities. However, first and last-mile connectivity problems are significant barriers to public transport ridership. Addressing first-mile and last-mile barriers may well reduce reliance on private cars and lead to a corresponding decrease in motorisation rates. Existing research has explored these factors; however, significant gaps remain as the approach overlooks explicit and implicit nuanced user experiences, especially those of car users. The scaler and relative influence of factors impacting first-mile and last-mile access, how car users perceive these issues and their impact on car usage are gaps to be explored. This study examines the factors influencing first and last-mile connections to public transport among car users who also use public transport. This study employs a framework to address this gap, integrating Exploratory Factor Analysis, Importance Performance Analysis and paired sample <em>t</em>-test to explore the interplay of first and last-mile factors. Findings indicate that safety while accessing bus stops, security at bus stops, pedestrian pathways or infrastructure, and proximity of bus stops, among other factors, are critical for improving overall satisfaction with first and last-mile connectivity for car users using public transport. More individuals walked when there was no alternative mode of transport, and individuals were more likely to choose ride-hailing for safety and convenience reasons. Implications of the results on practice and future research are explored.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"126 ","pages":"Article 104240"},"PeriodicalIF":5.7,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Securing power grids and charging infrastructure: Cyberattack resilience and vehicle-to-grid integration","authors":"Hamid R. Sayarshad","doi":"10.1016/j.jtrangeo.2025.104231","DOIUrl":"10.1016/j.jtrangeo.2025.104231","url":null,"abstract":"<div><div>The increasing interconnectivity of power grids and electric vehicle (EV) charging stations exposes them to the ever-growing threat of cyberattacks. This paper proposes a multifaceted approach that addresses the interdependencies between power grids, charging stations, and EVs. We explore a new EV routing challenge that includes regulations for charging and vehicle-to-grid (V2G) discharging. We estimate charging demands by analyzing EV usage patterns, charging/discharging plans, charging station availability, and user preferences such as routing and driver anxiety. The study explores a new EV charging optimization scenario considering charging costs, traffic, travel time, and setup time. A vital aspect of the proposed model is its ability to facilitate bidirectional energy flow between EVs and the power grid. This strategy enhances grid stability and facilitates efficient energy management, with charging stations actively participating in load balancing, peak shaving, and grid stabilization during a cyberattack. Furthermore, we formulate a network interdiction problem that strategically removes specific links in the power network to prevent the spread of a cyberattack. The effectiveness of the proposed approach is evaluated through five case studies. The findings suggest that the proposed hybrid planning solution (Case 5) is the most effective strategy. It successfully achieves zero load-shedding, reduces the charging and discharging constraints for electric vehicles (EVs), and eliminates susceptible nodes.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"126 ","pages":"Article 104231"},"PeriodicalIF":5.7,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A neuro-fuzzy and deep learning framework for accurate public transport demand forecasting: Leveraging spatial and temporal factors","authors":"Shariat Radfar ,&nbsp;Hamidreza Koosha ,&nbsp;Ali Gholami ,&nbsp;Atefeh Amindoust","doi":"10.1016/j.jtrangeo.2025.104217","DOIUrl":"10.1016/j.jtrangeo.2025.104217","url":null,"abstract":"<div><div>Efficient public transportation requires innovative planning and operational strategies. Accurate demand forecasting is crucial, as it is influenced by complex, non-linear interactions of various spatial and temporal factors. This study proposes a neuro-fuzzy inference and deep learning models to predict public transport demand in Mashhad's traffic zones for enhanced operational planning. The model's flexibility allows the integration of diverse temporal and spatial variables. Four Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Long Short-Term Memory (LSTM) models developed with two datasets were evaluated and compared to each other. Datasets one and two contained all possible variables without pre-judging their impact, encompassing daily and yearly horizons, respectively. Datasets three and four employed the identified influential variables from previous datasets using the Random Forest algorithm, leading to faster processing and reduced error. Five statistical coefficients including MSE (Mean Squared Error), BIAS, R² (Coefficient of Determination), WI (Willmott Index) and NSE (Nash-Sutcliffe Efficiency were presented to evaluate the performance of the proposed models. The results showed that the LSTM neural network model in the short-term daily scale (MSE = 0.0006, BIAS = 0.9308, R² = 0.9047, WI = 0.7591, NSE = 0.9047) and the ANFIS model in the long-term annual scale (MSE = 0.0024, BIAS = 0.0229, R² = 0.9415, WI = 0.9730, NSE = 0.8738) achieved superior performance in predicting demand for bus and rail systems in Mashhad. This research's forecasting models enable planners to estimate public transport demand under varying utilization levels of urban uses in Mashhad, offering insights for both daily and annual horizons across different traffic zones.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"126 ","pages":"Article 104217"},"PeriodicalIF":5.7,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transport quality and user perception: Effect of bus station hedonic quality on student trip behavior","authors":"Armando Cartenì ,&nbsp;Ilaria Henke ,&nbsp;Antonella Falanga ,&nbsp;Mariarosaria Picone","doi":"10.1016/j.jtrangeo.2025.104235","DOIUrl":"10.1016/j.jtrangeo.2025.104235","url":null,"abstract":"<div><div>This study examines the impact of bus station quality on users' travel choices, with a specific focus on the hedonic aspects related to architectural design and passenger services offered. It is widely shown that a safer, reliable, and comfortable transport service fosters greater trust in the transport system and leaves users with a positive perception of ease of movement within a geographical area. Moreover, the quality of public transport services has long been recognized as a crucial factor in shaping perception of accessibility to a place, potentially expanding the catchment area by attracting a larger number of users. In designing new terminals, many planners worldwide specifically focus on hedonic (aesthetic) aspects, also influencing the user's quality perception. Unlike rail stations, bus stations have had little attention with respect to aesthetic quality and passenger services, even if many studies have highlighted the significant impact that the design, services, and amenities of bus waiting areas have on user satisfaction. This study focuses on the hedonic value of a bus station and estimates users' willingness to pay (WTP) for enhanced station quality. The research targets are university students (aged 18–25) traveling on extra-urban routes, involving three major Italian cities: Milan, Rome, and Naples. Using a Discrete Choice Experiment (DCE) conducted through a Virtual Reality (VR) immersive experience, this study explores users' willingness to switch from a conventional bus station to a newly designed high-quality one, assessed in terms of both architectural standards (i.e. the “beauty”) and the functional quality (i.e. passenger's services offered, like restaurant, bar, free Wi-Fi, shops, comfortable waiting room, e-ticketing devices). Analyzing various cost and travel time SP scenarios, the model results shows that the average Italian student is willing to pay an additional €3.11 per trip (equivalent to 25 % of the actual average trip cost) or extend their travel time by up to 20.9 min per trip (26 % of the average actual travel time) to experience a superior bus station instead of a traditional one. The practical implications of this study are clear for urban planners, policymakers, and transport authorities: prioritizing investments in high-quality stations can significantly improve passenger satisfaction and promote greater use of public transport.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"126 ","pages":"Article 104235"},"PeriodicalIF":5.7,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social inclusion in sustainable urban mobility plans (SUMPs): The case of shared mobility in Utrecht, the Netherlands","authors":"Jasmijn van der Craats ,&nbsp;Dea van Lierop ,&nbsp;David Duran-Rodas","doi":"10.1016/j.jtrangeo.2025.104234","DOIUrl":"10.1016/j.jtrangeo.2025.104234","url":null,"abstract":"<div><div>This article explores the social inclusiveness of Sustainable Urban Mobility Plans (SUMPs), a policy tool introduced by the European Commission to inspire local governments in developing long-term sustainable visions to address the mobility needs of everyone. The aim of SUMPs is to accelerate the shift to sustainable mobility and achieve the complete decarbonisation of European Mobility by 2050. While the rationale behind SUMPs is that local governments understand the needs of their inhabitants and visitors, concerns have arisen regarding their capacity to recognise socially disadvantaged groups, potentially exacerbating social inequalities. Socially disadvantaged groups are prone to transport poverty, limiting their access to essential services and societal participation. Using a mixed-method approach, we analyse the social inclusiveness of SUMPs, focusing on Utrecht, the Netherlands. We conduct a qualitative analysis of policy documents to provide contextual understanding and assess the inclusion of socially disadvantaged groups within SUMPs. Our findings indicate that SUMPs recognise diverse social groups, including individuals with disabilities, children, older adults, and low-income groups, and acknowledge shared mobility as a tool to reduce transport poverty. We then develop a social indicator based on the identified socially disadvantaged groups to compare their distribution with the availability of shared mobility services. These are mapped for both 2019 and 2023, drawing on the municipality of Utrecht's 2020 action plan for shared mobility, which explicitly emphasises the role of shared mobility in reducing transport poverty by improving their availability for socially disadvantaged groups. Our study highlights that neighbourhoods with low social indicators are concentrated in the outskirts of the city, whereas shared mobility services are predominantly available in the city centre. Consequently, the ambition outlined in the documents regarding shared mobility's potential to reduce transport poverty has not yet materialized in the real world. This study provides insight into the capacity of SUMPs to address social inclusion issues, offering valuable guidance for the development of effective and socially inclusive sustainable mobility policies in European cities.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"126 ","pages":"Article 104234"},"PeriodicalIF":5.7,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of high-risk areas using the interpretable machine learning: Based on each determinant for the severity of pedestrian crashes","authors":"Junho Yoon","doi":"10.1016/j.jtrangeo.2025.104216","DOIUrl":"10.1016/j.jtrangeo.2025.104216","url":null,"abstract":"<div><div>Despite the steady decline in the total number of pedestrian crashes in Korea, the pedestrian fatality rate per 100,000 people remains high compared to the Organization for Economic Cooperation and Development (OECD) average. As the data of traffic crashes is gradually accumulated every year, various machine learning methodologies are needed to analyze this data. This study proposed a new algorithmic approach using Local Interpretable Model-Agnostic Explanation (LIME) to identify vulnerable pedestrian crash areas based on each determinant influencing these severity in Seoul. Using the pedestrian crash data from 2016 to 2018, this study uses the XGBoost to model the determinants of pedestrian crash severity and LIME to predict high-risk areas for each determinant. A new algorithmic approach using LIME was proposed to enhance the reliability by filtering data based on an Explanation Fit (R² ≥ 0.26), in reference to <span><span>Cohen (1988)</span></span>. Upon synthesizing the results, Cheongnyangni Station and Gangnam Station in Seoul were predicted as vulnerable to severe pedestrian crashes due to the superposition of influencing variables considered in this study. In this study, the heatmap predictions derived from the proposed algorithm methodology provided insights into the vulnerable areas and non-linear determinants of pedestrian crash severity. Additionally, this study suggests policy implications aimed at reducing pedestrian crash severity and enhancing pedestrian safety.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"126 ","pages":"Article 104216"},"PeriodicalIF":5.7,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143808493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}