Pub Date : 2026-01-01Epub Date: 2025-12-19DOI: 10.1016/j.jpubtr.2025.100146
Nikolaus Stratil-Sauer, Nils Breyer
Reliability plays a key role in the experience of a rail traveler. The reliability of journeys involving transfers is affected by the reliability of the transfers and the consequences of missing a transfer, as well as the possible delay of the train used to reach the destination. In this paper, we propose a flexible method to model the reliability of train journeys with any number of transfers. The method combines a transfer reliability model based on gradient boosting, responsible for predicting the reliability of transfers between trains, and a delay model based on probabilistic Bayesian regression, which is used to model train arrival delays. The models are trained on delay data from four Swedish train stations and evaluated on delay data from another two stations, in order to evaluate the generalization performance of the models. We show that the probabilistic delay model, which models train delays following a mixture distribution with two lognormal components, allows to much more realistically model the distribution of actual train delays compared to a standard lognormal model. Finally, we show how these models can be used together to predict the arrival delay distribution at the final destination of the journey. The results indicate that the method accurately predicts the reliability for nine out of ten tested journeys. The method could be used to improve journey planners by providing reliability information to travelers. Further applications include timetable planning and transport modeling.
{"title":"Probabilistic modeling of delays for train journeys with transfers","authors":"Nikolaus Stratil-Sauer, Nils Breyer","doi":"10.1016/j.jpubtr.2025.100146","DOIUrl":"10.1016/j.jpubtr.2025.100146","url":null,"abstract":"<div><div>Reliability plays a key role in the experience of a rail traveler. The reliability of journeys involving transfers is affected by the reliability of the transfers and the consequences of missing a transfer, as well as the possible delay of the train used to reach the destination. In this paper, we propose a flexible method to model the reliability of train journeys with any number of transfers. The method combines a transfer reliability model based on gradient boosting, responsible for predicting the reliability of transfers between trains, and a delay model based on probabilistic Bayesian regression, which is used to model train arrival delays. The models are trained on delay data from four Swedish train stations and evaluated on delay data from another two stations, in order to evaluate the generalization performance of the models. We show that the probabilistic delay model, which models train delays following a mixture distribution with two lognormal components, allows to much more realistically model the distribution of actual train delays compared to a standard lognormal model. Finally, we show how these models can be used together to predict the arrival delay distribution at the final destination of the journey. The results indicate that the method accurately predicts the reliability for nine out of ten tested journeys. The method could be used to improve journey planners by providing reliability information to travelers. Further applications include timetable planning and transport modeling.</div></div>","PeriodicalId":47173,"journal":{"name":"Journal of Public Transportation","volume":"28 ","pages":"Article 100146"},"PeriodicalIF":2.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145799801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-02-01DOI: 10.1016/j.jpubtr.2025.100117
Zhenlin Qin , Pengfei Zhang , Leizhen Wang , Zhenliang Ma
Large language models (LLMs) showed superior performance in many language-related tasks. It is promising to model the individual mobility prediction problem as a language model and use pretrained LLMs to predict the individual next trip information (e.g., time and location) for personalized travel recommendations. Theoretically, it is expected to overcome the common limitations of data-driven prediction models in zero/few shot learning, generalization, and interpretability. The paper proposes a LingoTrip model for predicting individual next trip location by designing the spatiotemporal context prompts for LLMs. The designed prompting strategies enable LLMs to capture implicit land use information (trip purposes), spatiotemporal mobility patterns (choice preferences), and geographical dependencies of the stations used (choice variability). The lingoTrip is validated using Hong Kong Mass Transit Railway trip data by comparing it with the state-of-the-art data-driven mobility prediction models under different training data sizes. Sensitivity analyses are performed for model hyperparameters and their tuning methods to adapt for other datasets. The results show that LingoTrip outperforms data-driven models in terms of prediction accuracy, transferability (between individuals), zero/few shot learning (limited training sample size) and interpretability of predictions. The LingoTrip model can facilitate the effective provision of personalized information for system crowding and disruption contexts (i.e., proactively providing information to targeted individuals).
{"title":"LingoTrip: Spatiotemporal context prompt driven large language model for individual trip prediction","authors":"Zhenlin Qin , Pengfei Zhang , Leizhen Wang , Zhenliang Ma","doi":"10.1016/j.jpubtr.2025.100117","DOIUrl":"10.1016/j.jpubtr.2025.100117","url":null,"abstract":"<div><div>Large language models (LLMs) showed superior performance in many language-related tasks. It is promising to model the individual mobility prediction problem as a language model and use pretrained LLMs to predict the individual next trip information (e.g., time and location) for personalized travel recommendations. Theoretically, it is expected to overcome the common limitations of data-driven prediction models in zero/few shot learning, generalization, and interpretability. The paper proposes a LingoTrip model for predicting individual next trip location by designing the spatiotemporal context prompts for LLMs. The designed prompting strategies enable LLMs to capture implicit land use information (trip purposes), spatiotemporal mobility patterns (choice preferences), and geographical dependencies of the stations used (choice variability). The lingoTrip is validated using Hong Kong Mass Transit Railway trip data by comparing it with the state-of-the-art data-driven mobility prediction models under different training data sizes. Sensitivity analyses are performed for model hyperparameters and their tuning methods to adapt for other datasets. The results show that LingoTrip outperforms data-driven models in terms of prediction accuracy, transferability (between individuals), zero/few shot learning (limited training sample size) and interpretability of predictions. The LingoTrip model can facilitate the effective provision of personalized information for system crowding and disruption contexts (i.e., proactively providing information to targeted individuals).</div></div>","PeriodicalId":47173,"journal":{"name":"Journal of Public Transportation","volume":"27 ","pages":"Article 100117"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-09-27DOI: 10.1016/j.jpubtr.2025.100140
Lancelot Rodrigue , Madhav G. Badami , Ahmed El-Geneidy
While public-transit fares can represent barriers to some people to use public-transit systems, they remain a major source of funding for operating it. Given the ubiquitous nature of fares in public-transit systems worldwide, understanding how characteristics of fare structures affect the distribution of fare burden (i.e., fare equity) is crucial. To do so we conducted a scoping review of the current literature on public-transit fare equity. We defined fare equity in the form of vertical equity (based on the ability-to-pay principle) and market equity (based on the beneficiary-pay principle). We then screened through 511 unique studies, retaining 24 for analysis. Findings were grouped based on fare attributes (e.g., distance-, time-, service- and user-based fare modulations), fare type and fare integration before combining results in a conceptual model. Distance-, time- and service-based fares were shown to have a positive effect on market equity while only income-based fares always positively impacted vertical equity. User-based fares have shown clear negative effects on market fare equity. The effects of most fare characteristics on fare equity were either not well researched or dependent on local contexts. Lastly, a lack of assessment of the synergies between fare characteristics in their effect on fare equity was also observed. Potential opposite effects of fare characteristics on vertical and market fare equity points to the necessity for public-transit agencies to choose which form of fare equity to promote. Recommendations for practitioners and researchers based on our findings are provided to guide the field of fare equity forward.
{"title":"Evaluating the effects of fare characteristics on fare equity: A scoping review","authors":"Lancelot Rodrigue , Madhav G. Badami , Ahmed El-Geneidy","doi":"10.1016/j.jpubtr.2025.100140","DOIUrl":"10.1016/j.jpubtr.2025.100140","url":null,"abstract":"<div><div>While public-transit fares can represent barriers to some people to use public-transit systems, they remain a major source of funding for operating it. Given the ubiquitous nature of fares in public-transit systems worldwide, understanding how characteristics of fare structures affect the distribution of fare burden (i.e., fare equity) is crucial. To do so we conducted a scoping review of the current literature on public-transit fare equity. We defined fare equity in the form of vertical equity (based on the ability-to-pay principle) and market equity (based on the beneficiary-pay principle). We then screened through 511 unique studies, retaining 24 for analysis. Findings were grouped based on fare attributes (e.g., distance-, time-, service- and user-based fare modulations), fare type and fare integration before combining results in a conceptual model. Distance-, time- and service-based fares were shown to have a positive effect on market equity while only income-based fares always positively impacted vertical equity. User-based fares have shown clear negative effects on market fare equity. The effects of most fare characteristics on fare equity were either not well researched or dependent on local contexts. Lastly, a lack of assessment of the synergies between fare characteristics in their effect on fare equity was also observed. Potential opposite effects of fare characteristics on vertical and market fare equity points to the necessity for public-transit agencies to choose which form of fare equity to promote. Recommendations for practitioners and researchers based on our findings are provided to guide the field of fare equity forward.</div></div>","PeriodicalId":47173,"journal":{"name":"Journal of Public Transportation","volume":"27 ","pages":"Article 100140"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bike sharing systems have the potential to significantly alleviate traffic congestion, reduce emissions and diminish reliance on parking facilities in city centers. One critical factor influencing the success of a bike sharing system is the effectiveness of rebalancing operations. These operations involve repositioning of the bikes at available stations through pickup and delivery activities performed by trucks, so that the anticipated user demand is satisfied. The Static Docked Bike Rebalancing Problem (SBRP) focuses on determining a cost-effective sequence of stations to be visited by trucks, along with the corresponding quantity of bikes to be picked up or delivered at each station. Deviating from past studies, we propose a new formulation for the SBRP problem which minimizes the cost of rebalancing operations, while factoring in the cost of unsatisfied user demand. The developed mathematical model is a mixed-integer nonlinear program, which is reformulated as a mixed-integer linear program. Lazy constraints and valid inequalities are introduced to improve performance and reduce computational times. A new set of problem instances is also generated based on benchmark problem instances from past studies. The applicability of the proposed methodology is also examined on a real case of the bike rebalancing problem, in the municipality of Penteli, a suburban area of Athens, Greece. The experimental findings demonstrate that the proposed model is capable of solving small scale instances to global optimality. Furthermore, the proposed heuristic manages to match the optimal solutions in very short computational times. To analyze the impact of the geographic distribution of station locations on the total cost of transportation of the rebalancing network, different computational experiments have been performed. The results obtained indicate that the stations’ geographic distribution has a significant impact on the total routing costs of the network.
{"title":"An exact approach for the static docked bike rebalancing problem that minimizes the routing costs and unmet demand under various geographic considerations","authors":"Aliki Pouliasi , Amalia Nikolopoulou , Konstantinos Gkiotsalitis , Konstantinos Kepaptsoglou","doi":"10.1016/j.jpubtr.2025.100141","DOIUrl":"10.1016/j.jpubtr.2025.100141","url":null,"abstract":"<div><div>Bike sharing systems have the potential to significantly alleviate traffic congestion, reduce emissions and diminish reliance on parking facilities in city centers. One critical factor influencing the success of a bike sharing system is the effectiveness of rebalancing operations. These operations involve repositioning of the bikes at available stations through pickup and delivery activities performed by trucks, so that the anticipated user demand is satisfied. The Static Docked Bike Rebalancing Problem (SBRP) focuses on determining a cost-effective sequence of stations to be visited by trucks, along with the corresponding quantity of bikes to be picked up or delivered at each station. Deviating from past studies, we propose a new formulation for the SBRP problem which minimizes the cost of rebalancing operations, while factoring in the cost of unsatisfied user demand. The developed mathematical model is a mixed-integer nonlinear program, which is reformulated as a mixed-integer linear program. Lazy constraints and valid inequalities are introduced to improve performance and reduce computational times. A new set of problem instances is also generated based on benchmark problem instances from past studies. The applicability of the proposed methodology is also examined on a real case of the bike rebalancing problem, in the municipality of Penteli, a suburban area of Athens, Greece. The experimental findings demonstrate that the proposed model is capable of solving small scale instances to global optimality. Furthermore, the proposed heuristic manages to match the optimal solutions in very short computational times. To analyze the impact of the geographic distribution of station locations on the total cost of transportation of the rebalancing network, different computational experiments have been performed. The results obtained indicate that the stations’ geographic distribution has a significant impact on the total routing costs of the network.</div></div>","PeriodicalId":47173,"journal":{"name":"Journal of Public Transportation","volume":"27 ","pages":"Article 100141"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145361991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-06-30DOI: 10.1016/j.jpubtr.2025.100130
Elisa Alfaro , Oscar Oviedo-Trespalacios , Francisco Alonso , Sergio A. Useche
Promoting public transport is widely regarded as a key strategy for advancing sustainability. However, concerns about women’s safety continue to pose a significant barrier to its regular use. A growing number of studies have highlighted the vulnerability of female commuters to harassment and crime, yet there is limited evidence on how these experiences –and the fears they generate– translate into changes in travel behavior. This knowledge gap makes it difficult to develop evidence-based interventions. Accordingly, this study examined the interrelations between sexual harassment, fear of crime, and travel-related behavioral adaptations among female public transport users in Spain. The analysis was based on a cross-sectional sample of 720 female public transport commuters. The average age of participants was 29 years. They responded to an e-survey addressing commuting patterns, perceptions of safety, and behavioral responses. Our results suggest that both direct and indirect experiences of harassment are consistently associated with higher levels of fear of crime, which in turn influence changes in travel behavior. Specifically, fear of crime was found to partially mediate the relationship between harassment and travel-related adaptations. These findings provide further insight into how psychological and contextual factors shape women’s use of public transport, and highlight the need to address not only actual incidents but also the broader perception of insecurity.
{"title":"Travel adaptations among women commuters in response to sexual harassment and fear of crime on public transport","authors":"Elisa Alfaro , Oscar Oviedo-Trespalacios , Francisco Alonso , Sergio A. Useche","doi":"10.1016/j.jpubtr.2025.100130","DOIUrl":"10.1016/j.jpubtr.2025.100130","url":null,"abstract":"<div><div>Promoting public transport is widely regarded as a key strategy for advancing sustainability. However, concerns about women’s safety continue to pose a significant barrier to its regular use. A growing number of studies have highlighted the vulnerability of female commuters to harassment and crime, yet there is limited evidence on how these experiences –and the fears they generate– translate into changes in travel behavior. This knowledge gap makes it difficult to develop evidence-based interventions. Accordingly, this study examined the interrelations between sexual harassment, fear of crime, and travel-related behavioral adaptations among female public transport users in Spain. The analysis was based on a cross-sectional sample of 720 female public transport commuters. The average age of participants was 29 years. They responded to an e-survey addressing commuting patterns, perceptions of safety, and behavioral responses. Our results suggest that both direct and indirect experiences of harassment are consistently associated with higher levels of fear of crime, which in turn influence changes in travel behavior. Specifically, fear of crime was found to partially mediate the relationship between harassment and travel-related adaptations. These findings provide further insight into how psychological and contextual factors shape women’s use of public transport, and highlight the need to address not only actual incidents but also the broader perception of insecurity.</div></div>","PeriodicalId":47173,"journal":{"name":"Journal of Public Transportation","volume":"27 ","pages":"Article 100130"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144517104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-11-18DOI: 10.1016/j.jpubtr.2025.100142
Hanna Vasiutina , Olha Shulika , Michał Bujak , Farnoud Ghasemi , Rafał Kucharski
On-demand feeder bus services present an innovative solution to urban mobility challenges, yet their success depends on a thorough assessment and strategic planning. Despite their potential, a systematic methodology for selecting suitable service areas remains underdeveloped. Simulation Framework for Feeder Location Evaluation (SimFLEX) utilizes spatial, demographic, and transportation-specific characteristics to conduct simulations at a microscopic level and compute various key performance indicators (KPIs), including service attractiveness, waiting time reduction, and added value. To address the stochastic nature of demand and uncertainty embedded in mode choice, we leverage Monte Carlo analysis, capturing variability across simulated scenarios. Our framework integrates several methods for a complete assessment of feeder potential: microscopic demand generation, creation of shared rides, public transport modeling, and iterative traveler learning and stabilization approach. Once the system stabilizes, KPIs are computed for comparative and sensitivity analyzes. As a showcase for our method, we apply SimFLEX to compare two remote districts in Krakow, Poland – Bronowice and Skotniki – designated as candidates for service deployment. Despite similar urban characteristics, our analysis revealed notable differences in KPIs between the analyzed areas: Skotniki exhibited higher service attractiveness (around 30 %) and added value (up to 7 %), whereas Bronowice showed greater potential for reducing waiting times (around 77 %). To assess the robustness of SimFLEX outputs under uncertain behavioral assumptions, we conducted a sensitivity analysis across a range of alternative-specific constants. The results consistently confirmed Skotniki as the more suitable candidate for feeder service implementation, demonstrating that this conclusion holds despite variations in a key preference parameter. The SimFLEX framework can be instrumental for decision makers to estimate feeder potential for a designated area. The model’s flexibility and modular characteristics make it a versatile tool for policymakers and urban planners to enhance urban mobility.
{"title":"SimFLEX: A methodology for comparative analysis of urban areas for implementing new on-demand feeder bus services","authors":"Hanna Vasiutina , Olha Shulika , Michał Bujak , Farnoud Ghasemi , Rafał Kucharski","doi":"10.1016/j.jpubtr.2025.100142","DOIUrl":"10.1016/j.jpubtr.2025.100142","url":null,"abstract":"<div><div>On-demand feeder bus services present an innovative solution to urban mobility challenges, yet their success depends on a thorough assessment and strategic planning. Despite their potential, a systematic methodology for selecting suitable service areas remains underdeveloped. Simulation Framework for Feeder Location Evaluation (SimFLEX) utilizes spatial, demographic, and transportation-specific characteristics to conduct simulations at a microscopic level and compute various key performance indicators (KPIs), including service attractiveness, waiting time reduction, and added value. To address the stochastic nature of demand and uncertainty embedded in mode choice, we leverage Monte Carlo analysis, capturing variability across simulated scenarios. Our framework integrates several methods for a complete assessment of feeder potential: microscopic demand generation, creation of shared rides, public transport modeling, and iterative traveler learning and stabilization approach. Once the system stabilizes, KPIs are computed for comparative and sensitivity analyzes. As a showcase for our method, we apply SimFLEX to compare two remote districts in Krakow, Poland – Bronowice and Skotniki – designated as candidates for service deployment. Despite similar urban characteristics, our analysis revealed notable differences in KPIs between the analyzed areas: Skotniki exhibited higher service attractiveness (around 30 %) and added value (up to 7 %), whereas Bronowice showed greater potential for reducing waiting times (around 77 %). To assess the robustness of SimFLEX outputs under uncertain behavioral assumptions, we conducted a sensitivity analysis across a range of alternative-specific constants. The results consistently confirmed Skotniki as the more suitable candidate for feeder service implementation, demonstrating that this conclusion holds despite variations in a key preference parameter. The SimFLEX framework can be instrumental for decision makers to estimate feeder potential for a designated area. The model’s flexibility and modular characteristics make it a versatile tool for policymakers and urban planners to enhance urban mobility.</div></div>","PeriodicalId":47173,"journal":{"name":"Journal of Public Transportation","volume":"27 ","pages":"Article 100142"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-02-05DOI: 10.1016/j.jpubtr.2025.100118
Julie A. King , Dominique A. Greer , Rae S.M. Danvers , Byron W. Keating
Travel on public transport for women is associated with concerns about safety from harassment and violence, and women may avoid public transport or make changes to their travel as a consequence. This qualitative research aimed to explore women’s experiences on public transport, the steps they take to avoid harassment and violence, and what they thought could be done to improve their safety. Women (n = 44) in Australia’s two largest cities, Sydney and Melbourne, were recruited for focus group discussions and their responses were analysed thematically. The results showed that women experience a personal safety burden, due to the need to anticipate possible exposure to harassment and violence, plan ways of avoiding or mitigating the risk, and use defensive tactics to cope with uncomfortable situations. This personal safety burden has five dimensions: cognitive, temporal, emotional, financial and social. The responses showed that women tended to take the public transport system as a given, and to believe they needed to take responsibility for their own safety, so that they did not nominate particular solutions for public transport providers to implement. However, it was evident that the features of public transport travel that participants felt were safer, such as the presence of trained staff, are diminishing with the move to greater use of technology and automation. It is considered that public transport providers have an obligation to ensure that women are not disadvantaged by the personal safety burden observed in this research. It is recommended that public transport providers note the existing features that women find safer (e.g., well-lit environment, presence of trained staff) and seek to extend their provision; and investigate innovative means of maintaining and enhancing safety for women while pursing technological change.
{"title":"The personal safety burden for women taking public transport in Australia and implications for provision of equitable public transport","authors":"Julie A. King , Dominique A. Greer , Rae S.M. Danvers , Byron W. Keating","doi":"10.1016/j.jpubtr.2025.100118","DOIUrl":"10.1016/j.jpubtr.2025.100118","url":null,"abstract":"<div><div>Travel on public transport for women is associated with concerns about safety from harassment and violence, and women may avoid public transport or make changes to their travel as a consequence. This qualitative research aimed to explore women’s experiences on public transport, the steps they take to avoid harassment and violence, and what they thought could be done to improve their safety. Women (n = 44) in Australia’s two largest cities, Sydney and Melbourne, were recruited for focus group discussions and their responses were analysed thematically. The results showed that women experience a personal safety burden, due to the need to anticipate possible exposure to harassment and violence, plan ways of avoiding or mitigating the risk, and use defensive tactics to cope with uncomfortable situations. This personal safety burden has five dimensions: cognitive, temporal, emotional, financial and social. The responses showed that women tended to take the public transport system as a given, and to believe they needed to take responsibility for their own safety, so that they did not nominate particular solutions for public transport providers to implement. However, it was evident that the features of public transport travel that participants felt were safer, such as the presence of trained staff, are diminishing with the move to greater use of technology and automation. It is considered that public transport providers have an obligation to ensure that women are not disadvantaged by the personal safety burden observed in this research. It is recommended that public transport providers note the existing features that women find safer (e.g., well-lit environment, presence of trained staff) and seek to extend their provision; and investigate innovative means of maintaining and enhancing safety for women while pursing technological change.</div></div>","PeriodicalId":47173,"journal":{"name":"Journal of Public Transportation","volume":"27 ","pages":"Article 100118"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143168293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-01-12DOI: 10.1016/j.jpubtr.2024.100115
Luis Enrique Ramos-Santiago , Luke Derochers
Mass transit is a key transport strategy in helping cities decarbonize, adapt to an era of rapid climate change, and guide rapid urbanization. Central to transit planning is the ability to accurately estimate demand for an effective, efficient, and equitable infrastructure and services. Instrumental to this effort is direct-demand modelling (DDM), which has evolved to become more nuanced in predicting ridership at station-level and station-to-station levels and in shedding light on key ridership and performance determinants. Local and Metropolitan accessibility as predictors of transit patronage has been shown significant in recent DDM studies at station-level, with an apparent synergistic relationship. This, however, has not been explored on a station-to-station passenger flow level. In several ways this is a more valid unit of analysis for rail ridership studies as it captures critical factors between and at both ends of the trip that are experienced by the passenger. It is also well documented that the sensitivity of passengers to key ridership determinants varies across income levels. In some jurisdictions income level strongly correlates with race/ethnicity and/or class, due in part to historical legacies of classism and/or racism. Segregation because of class and/or race prejudice, often found in US cities, might yield spatial heterogeneity in whole-network DDM model parameters and introduce bias that could potentially mislead transit analysts, policy makers, and systemwide effectiveness. We explored and tested these possibilities and considered modelling and policy implications as we leveraged Atlanta’s legacy of racial and income segregation in studying MARTA’s Origin-Destination (O-D) passenger flow patterns. First, a potential synergistic relationship between origin-stations’ and destination-stations’ walking accessibility levels was tested. Disparities, if any, in this and other ridership determinants were then explored between two distinct sets of O-D pairs whose origin Pedsheds accommodate majority-white or majority-nonwhite residents. Comparison and testing using generalized crossed-effects modelling reveals important differences in fit, magnitude, and significance of some parameters across submodels and as compared to the whole-network model. We also identified distinct moderating effects of distance between O-D pair stations and walking accessibility levels across submodels. In racially- and/or class-segregated cities planners would benefit from developing race- and/or class-based DDM submodels that would likely yield less biassed parameters; improve our understanding of rail transit patronage determinants; and help in crafting more effective and equitable transit and land-use policies.
{"title":"The influence of walking accessibility on station-to-station passenger flow and its interaction with metropolitan race/class segregation: A case study of MARTA’s heavy-rail network, Atlanta (USA)","authors":"Luis Enrique Ramos-Santiago , Luke Derochers","doi":"10.1016/j.jpubtr.2024.100115","DOIUrl":"10.1016/j.jpubtr.2024.100115","url":null,"abstract":"<div><div>Mass transit is a key transport strategy in helping cities decarbonize, adapt to an era of rapid climate change, and guide rapid urbanization. Central to transit planning is the ability to accurately estimate demand for an effective, efficient, and equitable infrastructure and services. Instrumental to this effort is direct-demand modelling (DDM), which has evolved to become more nuanced in predicting ridership at station-level and station-<em>to</em>-station levels and in shedding light on key ridership and performance determinants. <em>Local</em> and <em>Metropolitan</em> accessibility as predictors of transit patronage has been shown significant in recent DDM studies at station-level, with an apparent synergistic relationship. This, however, has not been explored on a station-<em>to</em>-station passenger flow level. In several ways this is a more valid unit of analysis for rail ridership studies as it captures critical factors between and at both ends of the trip that are experienced by the passenger. It is also well documented that the sensitivity of passengers to key ridership determinants varies across income levels. In some jurisdictions income level strongly correlates with race/ethnicity and/or class, due in part to historical legacies of classism and/or racism. Segregation because of class and/or race prejudice, often found in US cities, might yield spatial heterogeneity in whole-network DDM model parameters and introduce bias that could potentially mislead transit analysts, policy makers, and systemwide effectiveness. We explored and tested these possibilities and considered modelling and policy implications as we leveraged Atlanta’s legacy of racial and income segregation in studying MARTA’s Origin-Destination (O-D) passenger flow patterns. First, a potential synergistic relationship between origin-stations’ and destination-stations’ walking accessibility levels was tested. Disparities, if any, in this and other ridership determinants were then explored between two distinct sets of O-D pairs whose origin Pedsheds accommodate majority-white or majority-nonwhite residents. Comparison and testing using generalized crossed-effects modelling reveals important differences in fit, magnitude, and significance of some parameters across submodels and as compared to the whole-network model. We also identified distinct moderating effects of distance between O-D pair stations and walking accessibility levels across submodels. In racially- and/or class-segregated cities planners would benefit from developing race- and/or class-based DDM submodels that would likely yield less biassed parameters; improve our understanding of rail transit patronage determinants; and help in crafting more effective and equitable transit and land-use policies.</div></div>","PeriodicalId":47173,"journal":{"name":"Journal of Public Transportation","volume":"27 ","pages":"Article 100115"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143168294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-06-21DOI: 10.1016/j.jpubtr.2025.100126
Marco Chitti , Paolo Beria
The paper examines the planning history of the Italian high-speed rail (HSR) network through three main perspectives: the distinction between service-driven and infrastructure-driven planning paradigms, the characteristics of infrastructure megaprojects, and the debates surrounding core and periphery regions. It divides this planning history into four key phases spanning nearly four decades, each marked by shifts in governance and planning philosophy. The paper evaluates the strengths and weaknesses of each phase, focusing not only on outcomes but also on the coherence of planning efforts. The Italian case serves as a basis for a broader discussion on the challenges of infrastructure-centered planning in rail transport.
{"title":"A planning history of high-speed rail in Italy","authors":"Marco Chitti , Paolo Beria","doi":"10.1016/j.jpubtr.2025.100126","DOIUrl":"10.1016/j.jpubtr.2025.100126","url":null,"abstract":"<div><div>The paper examines the planning history of the Italian high-speed rail (HSR) network through three main perspectives: the distinction between service-driven and infrastructure-driven planning paradigms, the characteristics of infrastructure megaprojects, and the debates surrounding core and periphery regions. It divides this planning history into four key phases spanning nearly four decades, each marked by shifts in governance and planning philosophy. The paper evaluates the strengths and weaknesses of each phase, focusing not only on outcomes but also on the coherence of planning efforts. The Italian case serves as a basis for a broader discussion on the challenges of infrastructure-centered planning in rail transport.</div></div>","PeriodicalId":47173,"journal":{"name":"Journal of Public Transportation","volume":"27 ","pages":"Article 100126"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144335719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-08-15DOI: 10.1016/j.jpubtr.2025.100135
Paul Redelmeier , Rodrigo Victoriano-Habit , Miles Crumley , Ahmed El-Geneidy
Bus Priority Interventions are small-scale changes that improve bus speed and reliability. These include changes to street geometry, bus stops, and traffic signals. Automated Vehicle Location-Automated Passenger Counting (AVL-APC) data can help transit agencies by providing insight into bus location, speed, and passenger volumes. This work proposes an end-to-end methodology for using AVL-APC data to create a concept design for bus priority interventions on a bus corridor. The proposed method is illustrated by analyzing a bus route in Portland, Oregon. This mixed-methods approach paired quantitative data analysis with site visits to identify what was causing delay on the route and suggest targeted interventions. Scenario analysis of historical trip data was employed to predict the impact of different interventions. Historical trips that fell into two different scenarios were compared: a delay scenario (where a specific delay-inducing event occurred, like a red light) and a non-delay scenario (where that event did not occur). This end-to-end methodology could be used by transit agencies and transportation planners to quickly assess different corridors and interventions, diagnose problems, and determine which projects would create the greatest customer and financial benefits. Employing this approach could help planners prioritize time and resources to ensure that the highest impact projects are pursued.
{"title":"Bit by bit: A method for using bus data to develop plan bus priority interventions in Portland, Oregon, USA","authors":"Paul Redelmeier , Rodrigo Victoriano-Habit , Miles Crumley , Ahmed El-Geneidy","doi":"10.1016/j.jpubtr.2025.100135","DOIUrl":"10.1016/j.jpubtr.2025.100135","url":null,"abstract":"<div><div>Bus Priority Interventions are small-scale changes that improve bus speed and reliability. These include changes to street geometry, bus stops, and traffic signals. Automated Vehicle Location-Automated Passenger Counting (AVL-APC) data can help transit agencies by providing insight into bus location, speed, and passenger volumes. This work proposes an end-to-end methodology for using AVL-APC data to create a concept design for bus priority interventions on a bus corridor. The proposed method is illustrated by analyzing a bus route in Portland, Oregon. This mixed-methods approach paired quantitative data analysis with site visits to identify what was causing delay on the route and suggest targeted interventions. Scenario analysis of historical trip data was employed to predict the impact of different interventions. Historical trips that fell into two different scenarios were compared: a delay scenario (where a specific delay-inducing event occurred, like a red light) and a non-delay scenario (where that event did not occur). This end-to-end methodology could be used by transit agencies and transportation planners to quickly assess different corridors and interventions, diagnose problems, and determine which projects would create the greatest customer and financial benefits. Employing this approach could help planners prioritize time and resources to ensure that the highest impact projects are pursued.</div></div>","PeriodicalId":47173,"journal":{"name":"Journal of Public Transportation","volume":"27 ","pages":"Article 100135"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144841898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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