Pub Date : 2025-06-01Epub Date: 2025-02-26DOI: 10.1016/j.jrtpm.2025.100515
Yu Rao , Qiangqiang Liu , Qingyuan Wang , Tianxiang Li , Mingyu Zhang
The key point for the energy-efficient train control (EETC) in a multi-train system is effectively utilizing the output power of other trains. However, obtaining the optimal solution of the EETC problem considering multi-train power flow requires high-precision calculation of the adjoint variables, which is time-consuming. In this paper, we revisit the problem and introduce a speed volatility functional to analyze the shape of the optimal speed profile and the corresponding optimal control modes for the train under different external power and track gradients. Based on this analysis, a fast-solving algorithm is devised. Case studies are conducted to validate our theoretical results, and demonstrate that the proposed algorithm achieves a significant improvement in computational speed (over 99%) compared to the global optimal algorithm (Rao et al., 2023a) while ensuring the energy saving effectiveness.
多列系统节能列车控制的关键是有效利用其他列车的输出功率。然而，考虑多列潮流的EETC问题的最优解需要高精度的伴随变量计算，耗时长。在本文中，我们重新审视了这个问题，并引入了一个速度波动函数来分析在不同外部功率和轨道梯度下列车的最优速度轮廓形状和相应的最优控制模式。在此基础上，设计了一种快速求解算法。通过实例研究验证了我们的理论结果，并证明了所提出的算法在保证节能效果的同时，与全局最优算法（Rao et al., 2023a）相比，计算速度显著提高（超过99%）。
{"title":"A new look at the shape characteristics of optimal speed profile for energy-efficient train control considering multi-train power flow","authors":"Yu Rao , Qiangqiang Liu , Qingyuan Wang , Tianxiang Li , Mingyu Zhang","doi":"10.1016/j.jrtpm.2025.100515","DOIUrl":"10.1016/j.jrtpm.2025.100515","url":null,"abstract":"<div><div>The key point for the energy-efficient train control (EETC) in a multi-train system is effectively utilizing the output power of other trains. However, obtaining the optimal solution of the EETC problem considering multi-train power flow requires high-precision calculation of the adjoint variables, which is time-consuming. In this paper, we revisit the problem and introduce a speed volatility functional to analyze the shape of the optimal speed profile and the corresponding optimal control modes for the train under different external power and track gradients. Based on this analysis, a fast-solving algorithm is devised. Case studies are conducted to validate our theoretical results, and demonstrate that the proposed algorithm achieves a significant improvement in computational speed (over 99%) compared to the global optimal algorithm (Rao et al., 2023a) while ensuring the energy saving effectiveness.</div></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"34 ","pages":"Article 100515"},"PeriodicalIF":2.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-03-06DOI: 10.1016/j.jrtpm.2025.100518
Ruifan Tang, Ronghui Liu, Zhiyuan Lin
Train delays can cause huge economic loss and passenger dissatisfaction. The Train Delay Prediction Problem has been investigated by a large number of studies. How to best represent certain features of a train is key to successful prediction. For instance, due to its complex topological nature, a train's route (i.e., origin, intermediate stations and destination) is one of the most difficult features to effectively represent. This study introduces graph embedding to understand and model the complex structure of a railway network which is able to capture a comprehensive collection of features including network topology, infrastructure and train profile. In particular, for the first time, we propose an approach to embed a train's route in a network topology perspective based on Structural Deep Network Embedding (SDNE) and Singular Value Decomposition (SVD). Compared to a conventional advanced method, Principle Component Analysis (PCA), our route embedding not only significantly reduces feature vector length and computational effort, but is also highly accurate and reliable in terms of capturing network topology as evidenced by K-means clustering. Computational experiments based on real-world cases from a UK train operator (TransPennine Express) show our graph-embedding based models are competitive in prediction accuracy and F1-score while are substantially computationally efficient compared to PCA.
{"title":"Predicting primary delay of train services using graph-embedding based machine learning","authors":"Ruifan Tang, Ronghui Liu, Zhiyuan Lin","doi":"10.1016/j.jrtpm.2025.100518","DOIUrl":"10.1016/j.jrtpm.2025.100518","url":null,"abstract":"<div><div>Train delays can cause huge economic loss and passenger dissatisfaction. The Train Delay Prediction Problem has been investigated by a large number of studies. How to best represent certain features of a train is key to successful prediction. For instance, due to its complex topological nature, a train's route (i.e., origin, intermediate stations and destination) is one of the most difficult features to effectively represent. This study introduces graph embedding to understand and model the complex structure of a railway network which is able to capture a comprehensive collection of features including network topology, infrastructure and train profile. In particular, for the first time, we propose an approach to embed a train's route in a network topology perspective based on Structural Deep Network Embedding (SDNE) and Singular Value Decomposition (SVD). Compared to a conventional advanced method, Principle Component Analysis (PCA), our route embedding not only significantly reduces feature vector length and computational effort, but is also highly accurate and reliable in terms of capturing network topology as evidenced by K-means clustering. Computational experiments based on real-world cases from a UK train operator (TransPennine Express) show our graph-embedding based models are competitive in prediction accuracy and F1-score while are substantially computationally efficient compared to PCA.</div></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"34 ","pages":"Article 100518"},"PeriodicalIF":2.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research aims to introduce a mathematical model capable of producing an optimal and coordinated timetable for the entire urban rail network to minimize passengers’ travel times and the trains’ energy consumption. The proposed model focuses on different speed profiles and a skip-stop strategy while considering the stochastic nature of passengers’ arrival and departure rates. This novel model can generate an optimal real-time schedule under variations in passenger demand. The implementation of a multi-agent deep deterministic policy gradient has been described, and it has been compared with a genetic algorithm. Eventually, this methodology is implemented on lines 1, 2, and 4 of Tehran’s metro network as a case study. The results indicate that using the skip-stop strategy and optimizing trains’ speed profiles along their paths can reduce the networks’ costs, including passengers’ waiting costs and the trains’ energy consumption costs, by 2.9% and 14.9%, respectively.
{"title":"Optimizing and synchronizing timetables in an urban subway network considering trains’ speed profiles and skip-stop strategy","authors":"Alireza Eslami , Yousef Shafahi , Shayan Bafandkar","doi":"10.1016/j.jrtpm.2025.100520","DOIUrl":"10.1016/j.jrtpm.2025.100520","url":null,"abstract":"<div><div>This research aims to introduce a mathematical model capable of producing an optimal and coordinated timetable for the entire urban rail network to minimize passengers’ travel times and the trains’ energy consumption. The proposed model focuses on different speed profiles and a skip-stop strategy while considering the stochastic nature of passengers’ arrival and departure rates. This novel model can generate an optimal real-time schedule under variations in passenger demand. The implementation of a multi-agent deep deterministic policy gradient has been described, and it has been compared with a genetic algorithm. Eventually, this methodology is implemented on lines 1, 2, and 4 of Tehran’s metro network as a case study. The results indicate that using the skip-stop strategy and optimizing trains’ speed profiles along their paths can reduce the networks’ costs, including passengers’ waiting costs and the trains’ energy consumption costs, by 2.9% and 14.9%, respectively.</div></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"34 ","pages":"Article 100520"},"PeriodicalIF":2.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143904051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-03-20DOI: 10.1016/j.jrtpm.2025.100517
Katarzyna Gawlak , Jarosław Konieczny , Krzysztof Domino , Jarosław Adam Miszczak
The impact of rail transport on the environment is one of the crucial factors for the sustainable development of this form of mass transport. We present a data-driven analysis of wild animal railway accidents in the region of southern Poland, a step to create the train driver warning system. We built our method by harnessing the Bayesian approach to the statistical analysis of information about the geolocation of the accidents. The implementation of the proposed model does not require advanced knowledge of data mining and can be applied even in less developed railway systems with small IT support. Furthermore, we have discovered unusual patterns of accidents while considering the number of trains and their speed and time at particular geographical locations of the railway network. We test the developed approach using data from southern Poland, compromising wildlife habitats and one of the most urbanised regions in Central Europe, based on this we conclude that our model is best suited to railway lines that pass through varying types of landscape.
{"title":"Statistical analysis of geoinformation data for increasing railway safety","authors":"Katarzyna Gawlak , Jarosław Konieczny , Krzysztof Domino , Jarosław Adam Miszczak","doi":"10.1016/j.jrtpm.2025.100517","DOIUrl":"10.1016/j.jrtpm.2025.100517","url":null,"abstract":"<div><div>The impact of rail transport on the environment is one of the crucial factors for the sustainable development of this form of mass transport. We present a data-driven analysis of wild animal railway accidents in the region of southern Poland, a step to create the train driver warning system. We built our method by harnessing the Bayesian approach to the statistical analysis of information about the geolocation of the accidents. The implementation of the proposed model does not require advanced knowledge of data mining and can be applied even in less developed railway systems with small IT support. Furthermore, we have discovered unusual patterns of accidents while considering the number of trains and their speed and time at particular geographical locations of the railway network. We test the developed approach using data from southern Poland, compromising wildlife habitats and one of the most urbanised regions in Central Europe, based on this we conclude that our model is best suited to railway lines that pass through varying types of landscape.</div></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"34 ","pages":"Article 100517"},"PeriodicalIF":2.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-03-08DOI: 10.1016/j.jrtpm.2025.100516
Arsen Benga , María Jesús Delgado Rodríguez , Sonia de Lucas Santos , Glediana Zeneli
Enhancing the efficiency of railways is key to the future of sustainable transport. The objective of this work is to identify leading railways in Europe, investigate sources of inefficiency, and guide underperformers towards best practices. We explore efficiency for some selected 21 prominent railways during 2016–2018 using Network Data Envelopment Analysis. The ranking obtained indicates averagely low efficiency scores, with slight improvements over time. Next, we build a performance matrix to determine the priority improvements for each company. The Tobit regression implies that the nation's wealth, length of haul, length of trip, and traffic density have a significantly positive relationship with the efficiency scores. We also observed no significant impact of companies' outputs on their efficiency scores, indicating that any minor decrease in transport demand is unlikely to impose significant constraints on efficiency scores.
{"title":"Efficiency analysis of European railway companies and the effect of demand reduction","authors":"Arsen Benga , María Jesús Delgado Rodríguez , Sonia de Lucas Santos , Glediana Zeneli","doi":"10.1016/j.jrtpm.2025.100516","DOIUrl":"10.1016/j.jrtpm.2025.100516","url":null,"abstract":"<div><div>Enhancing the efficiency of railways is key to the future of sustainable transport. The objective of this work is to identify leading railways in Europe, investigate sources of inefficiency, and guide underperformers towards best practices. We explore efficiency for some selected 21 prominent railways during 2016–2018 using Network Data Envelopment Analysis. The ranking obtained indicates averagely low efficiency scores, with slight improvements over time. Next, we build a performance matrix to determine the priority improvements for each company. The Tobit regression implies that the nation's wealth, length of haul, length of trip, and traffic density have a significantly positive relationship with the efficiency scores. We also observed no significant impact of companies' outputs on their efficiency scores, indicating that any minor decrease in transport demand is unlikely to impose significant constraints on efficiency scores.</div></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"34 ","pages":"Article 100516"},"PeriodicalIF":2.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-04-02DOI: 10.1016/j.jrtpm.2025.100519
Jinhua Lyu, Jonathan F. Bard
Freight rail engineers and conductors have long faced unpredictable and inflexible work schedules, leading to on-the-job fatigue, compromised safety, and poor work-life balance. This paper aims to construct robust weekly schedules for these crew members to alleviate the pressures associated with irregular and unpredictable work hours. The scheduling problem is formulated as a multi-commodity network flow problem on a directed time-space graph. Both two-city and three-city districts are addressed. To account for the variability in travel times, a set of scenarios is defined in which demand is increased by up to 20% to build slack into the schedules. The results are validated using Monte Carlo simulation where 100 random weekly instances are generated for each city pair and key performance metrics assessed. Major findings show that (i) optimal weekly schedules can be constructed in minutes for engineers in crew districts with two cities, and in several hours for engineers in crew districts with three cities, (ii) different percentages of demand increase significantly affect the degree of robustness, and (iii) forming crew districts with three cities rather than two gives better results in terms of required number of engineers and trip coverage rates.
{"title":"Weekly crew scheduling for freight rail engineers: A network approach","authors":"Jinhua Lyu, Jonathan F. Bard","doi":"10.1016/j.jrtpm.2025.100519","DOIUrl":"10.1016/j.jrtpm.2025.100519","url":null,"abstract":"<div><div>Freight rail engineers and conductors have long faced unpredictable and inflexible work schedules, leading to on-the-job fatigue, compromised safety, and poor work-life balance. This paper aims to construct robust weekly schedules for these crew members to alleviate the pressures associated with irregular and unpredictable work hours. The scheduling problem is formulated as a multi-commodity network flow problem on a directed time-space graph. Both two-city and three-city districts are addressed. To account for the variability in travel times, a set of scenarios is defined in which demand is increased by up to 20% to build slack into the schedules. The results are validated using Monte Carlo simulation where 100 random weekly instances are generated for each city pair and key performance metrics assessed. Major findings show that (i) optimal weekly schedules can be constructed in minutes for engineers in crew districts with two cities, and in several hours for engineers in crew districts with three cities, (ii) different percentages of demand increase significantly affect the degree of robustness, and (iii) forming crew districts with three cities rather than two gives better results in terms of required number of engineers and trip coverage rates.</div></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"34 ","pages":"Article 100519"},"PeriodicalIF":2.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-05-17DOI: 10.1016/j.jrtpm.2025.100521
Mátyás Koniorczyk , Krzysztof Krawiec , Ludmila Botelho , Nikola Bešinović , Krzysztof Domino
We address the applicability of a hybrid quantum–classical heuristics for practical railway rescheduling management problems. We build an integer linear programming model and solve it with D-Wave’s quantum–classical hybrid solver (CQM) as well as with CPLEX, for comparison. The proposed approach is demonstrated on a real-life heterogeneous urban network in Poland, including both single- and multi-track segments. All the requirements posed by the operator of the network are included in the model. The computational results demonstrate the readiness for application and the benefits of quantum–classical hybrid solvers in a realistic railway scenario: they yield acceptable solutions on time, which is a critical requirement in a rescheduling situation. In particular, CQM as a probabilistic heuristic solver provides a number of feasible, close-to-optimal solutions the dispatcher can choose from.
{"title":"Solving rescheduling problems in heterogeneous urban railway networks using hybrid quantum–classical approach","authors":"Mátyás Koniorczyk , Krzysztof Krawiec , Ludmila Botelho , Nikola Bešinović , Krzysztof Domino","doi":"10.1016/j.jrtpm.2025.100521","DOIUrl":"10.1016/j.jrtpm.2025.100521","url":null,"abstract":"<div><div>We address the applicability of a hybrid quantum–classical heuristics for practical railway rescheduling management problems. We build an integer linear programming model and solve it with D-Wave’s quantum–classical hybrid solver (CQM) as well as with CPLEX, for comparison. The proposed approach is demonstrated on a real-life heterogeneous urban network in Poland, including both single- and multi-track segments. All the requirements posed by the operator of the network are included in the model. The computational results demonstrate the readiness for application and the benefits of quantum–classical hybrid solvers in a realistic railway scenario: they yield acceptable solutions on time, which is a critical requirement in a rescheduling situation. In particular, CQM as a probabilistic heuristic solver provides a number of feasible, close-to-optimal solutions the dispatcher can choose from.</div></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"34 ","pages":"Article 100521"},"PeriodicalIF":2.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01Epub Date: 2025-01-07DOI: 10.1016/j.jrtpm.2024.100503
Shengzhong Ji, Mingjun Ji, Zhendi Gao, Lingrui Kong, Jialu Ji
This paper investigates the optimization problem of sea-rail intermodal container collection and distribution operations under novel port layout where railway lines extend to the quayside. It integrates optimization train scheduling and container transshipment to enhance temporal and spatial coordination between trains and vessels. The objectives include maximizing the ratio of direct transshipment of import/export containers and minimizing the total operational time of trains at the quayside operational area. A nonlinear mixed-integer bi-objective optimization model is constructed and linearized for compatibility with commercial solvers. Different instance sizes have been analyzed and validated, demonstrating the model’s efficiency with average direct transshipment ratios exceeding 85.47%. Furthermore, the rational allocation of mechanical equipment, such as rail-mounted gantry and quay cranes, can maximize direct transfer rates and avoid resource wastage. The optimization method proposed in this paper not only reduces port operational costs but also offers valuable insights for port layout planning.
{"title":"Optimization of sea-rail intermodal container collection and distribution under novel port layout","authors":"Shengzhong Ji, Mingjun Ji, Zhendi Gao, Lingrui Kong, Jialu Ji","doi":"10.1016/j.jrtpm.2024.100503","DOIUrl":"10.1016/j.jrtpm.2024.100503","url":null,"abstract":"<div><div>This paper investigates the optimization problem of sea-rail intermodal container collection and distribution operations under novel port layout where railway lines extend to the quayside. It integrates optimization train scheduling and container transshipment to enhance temporal and spatial coordination between trains and vessels. The objectives include maximizing the ratio of direct transshipment of import/export containers and minimizing the total operational time of trains at the quayside operational area. A nonlinear mixed-integer bi-objective optimization model is constructed and linearized for compatibility with commercial solvers. Different instance sizes have been analyzed and validated, demonstrating the model’s efficiency with average direct transshipment ratios exceeding 85.47%. Furthermore, the rational allocation of mechanical equipment, such as rail-mounted gantry and quay cranes, can maximize direct transfer rates and avoid resource wastage. The optimization method proposed in this paper not only reduces port operational costs but also offers valuable insights for port layout planning.</div></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"33 ","pages":"Article 100503"},"PeriodicalIF":2.6,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143146651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01Epub Date: 2025-02-14DOI: 10.1016/j.jrtpm.2025.100507
Yannian Lee
Following two consecutive catastrophic railway accidents in Taiwan, public safety concern has been raised in railway transportation services. To improve train operation safety, this study integrates the Human Factors Analysis and Classification System (HFACS), Fuzzy Logic Modeling (FLM) method, and Human Factors Intervention Matrix (HFIX) to develop a safety assessment framework. Twenty eight major railway occurrence investigation reports published by the Taiwan Transportation Safety Board are collected for data extraction. Using the HFACS, causal factors causing major railway occurrences are first classified, followed by critical causal factors identification through FLM method. The HFIX is applied to categorized safety recommendations which were issued based on the identified causal factors of occurrence investigations and pair the results with critical causal factors for accident rate evaluations and effectiveness assessment. The evaluations reveal that the statistical accident rate in 2023 was higher than the predicted accident rate. The results also reveal that mitigating the frequency of identified causal factors is more efficient for occurrences reduction than through safety recommendations enforcement. Therefore, decision makers can determine the best intervention strategies based on available resources and develop relevant countermeasures for implementation.
{"title":"A new approach to identify critical causal factors and evaluate intervention strategies for mitigating major railway occurrences in Taiwan","authors":"Yannian Lee","doi":"10.1016/j.jrtpm.2025.100507","DOIUrl":"10.1016/j.jrtpm.2025.100507","url":null,"abstract":"<div><div>Following two consecutive catastrophic railway accidents in Taiwan, public safety concern has been raised in railway transportation services. To improve train operation safety, this study integrates the Human Factors Analysis and Classification System (HFACS), Fuzzy Logic Modeling (FLM) method, and Human Factors Intervention Matrix (HFIX) to develop a safety assessment framework. Twenty eight major railway occurrence investigation reports published by the Taiwan Transportation Safety Board are collected for data extraction. Using the HFACS, causal factors causing major railway occurrences are first classified, followed by critical causal factors identification through FLM method. The HFIX is applied to categorized safety recommendations which were issued based on the identified causal factors of occurrence investigations and pair the results with critical causal factors for accident rate evaluations and effectiveness assessment. The evaluations reveal that the statistical accident rate in 2023 was higher than the predicted accident rate. The results also reveal that mitigating the frequency of identified causal factors is more efficient for occurrences reduction than through safety recommendations enforcement. Therefore, decision makers can determine the best intervention strategies based on available resources and develop relevant countermeasures for implementation.</div></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"33 ","pages":"Article 100507"},"PeriodicalIF":2.6,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01Epub Date: 2025-01-13DOI: 10.1016/j.jrtpm.2025.100504
Miguel I. Grilo, Gonçalo F. Neves, Guilherme Ribeiro, Virgínia Infante, António R. Andrade
Unauthorized ‘Signals Passed At Danger’ (SPADs) are common accident precursors in the Portuguese railways. Critical events in the past highlight the need to assess the risk posed by SPADs. This study proposes a quantitative risk assessment of SPADs in Portugal as a decision support tool, utilizing a three-step procedure, and data from 2016 to 2021. The first step involves statistically modeling the SPAD frequency, including the spatio-temporal and operational factors using Generalized Linear Models, such as Binomial and Poisson regressions. The Binomial models exhibit the best goodness-of-fit statistics. The second step involves statistically modeling the severity of SPADs and creating a severity prediction model based on incident-related data, with Ordinal and Multinomial models compared for prediction performance. Finally, the risk is assessed by estimating the cost magnitude for one year. Additionally, the influence of the Automatic Train Protection (ATP) system on SPAD risk is evaluated. The findings suggest that a fully operational ATP system could further reduce SPAD risk by 19%. This study highlights the importance of considering SPAD risk for safe and efficient railway operations. The results of this risk assessment can support decision-makers in prioritizing prevention and mitigation measures to improve railway operational safety.
{"title":"Enhancing railway operational safety: A quantitative risk assessment of signals passed at danger","authors":"Miguel I. Grilo, Gonçalo F. Neves, Guilherme Ribeiro, Virgínia Infante, António R. Andrade","doi":"10.1016/j.jrtpm.2025.100504","DOIUrl":"10.1016/j.jrtpm.2025.100504","url":null,"abstract":"<div><div>Unauthorized ‘Signals Passed At Danger’ (SPADs) are common accident precursors in the Portuguese railways. Critical events in the past highlight the need to assess the risk posed by SPADs. This study proposes a quantitative risk assessment of SPADs in Portugal as a decision support tool, utilizing a three-step procedure, and data from 2016 to 2021. The first step involves statistically modeling the SPAD frequency, including the spatio-temporal and operational factors using Generalized Linear Models, such as Binomial and Poisson regressions. The Binomial models exhibit the best goodness-of-fit statistics. The second step involves statistically modeling the severity of SPADs and creating a severity prediction model based on incident-related data, with Ordinal and Multinomial models compared for prediction performance. Finally, the risk is assessed by estimating the cost magnitude for one year. Additionally, the influence of the Automatic Train Protection (ATP) system on SPAD risk is evaluated. The findings suggest that a fully operational ATP system could further reduce SPAD risk by 19%. This study highlights the importance of considering SPAD risk for safe and efficient railway operations. The results of this risk assessment can support decision-makers in prioritizing prevention and mitigation measures to improve railway operational safety.</div></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"33 ","pages":"Article 100504"},"PeriodicalIF":2.6,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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