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Railway transport in the Czech Republic largely uses transit corridors, which are significantly more used than the rest of the railway network. This assumption leads to an increase in the safety of these lines and gradual double-tracking. All these aspects lead to the fact that the given lines are controlled from dispatching centres, while other lines are controlled from regional dispatch offices. The above parameters also apply to other non-corridor but still busy lines. It can therefore be concluded that this trend of remote control brings significant operational and technological advantages. The most visible benefit is the personnel saving of operational employees, but another significant benefit, which is not so obvious at first glance, is the benefit of a more efficient organization and management of railway transport. This impact brings the effect of smoother traffic, which manifests itself in a lower burden on the environment, thanks to fewer train starts and stops, or there will be no complete stop, but only a reduction in train speed. Furthermore, this influence is evident in the more frequent overtaking of trains not in railway stations, but in inter-station sections. All these advantages lead to an increase in an important operational indicator, which is the throughput of the track. [ABSTRACT FROM AUTHOR]

Out-of-gauge trains are trains with loading freight that exceeds the loading limitation border. Considering collision avoidance, the out-of-gauge trains have speed restriction of their own, and the trains running on the parallel track. Therefore, it is necessary to execute a train rescheduling procedure to rearrange the train paths of the out-of-gauge trains and the affected trains based on the fundamental timetable. For rescheduling the timetable, considering the blockades and the speed restrictions caused by the out-of-gauge trains, this paper proposed a time-space-state network representation for describing the out-of-gauge train rescheduling problem. A novel concept, speed allowance, is introduced to describe the train speed restriction due to the out-of-gauge trains. An integer programming model based on the time-space network is proposed to minimize the total train delay when running the out-of-gauge trains. The model can be solved by the rolling-time horizon approach for reducing computational time. A numerical example is conducted based on the conventional railway in China, demonstrating the solution performance of the model and the practical use of the methodology. Gurobi solver cannot obtain an optimal solution within 1 h when the planning-time horizon is greater than 120 min. With the rolling-time horizon approach, the rescheduled timetable can be obtained within 124 s for the 300 min planning-time horizon using 180 min rolling-time window. [ABSTRACT FROM AUTHOR]

Out-of-gauge trains are trains with loading freight that exceeds the loading limitation border. Considering collision avoidance, the out-of-gauge trains have speed restriction of their own, and the trains running on the parallel track. Therefore, it is necessary to execute a train rescheduling procedure to rearrange the train paths of the out-of-gauge trains and the affected trains based on the fundamental timetable. For rescheduling the timetable, considering the blockades and the speed restrictions caused by the out-of-gauge trains, this paper proposed a time-space-state network representation for describing the out-of-gauge train rescheduling problem. A novel concept, speed allowance, is introduced to describe the train speed restriction due to the out-of-gauge trains. An integer programming model based on the time-space network is proposed to minimize the total train delay when running the out-of-gauge trains. The model can be solved by the rolling-time horizon approach for reducing computational time. A numerical example is conducted based on the conventional railway in China, demonstrating the solution performance of the model and the practical use of the methodology. Gurobi solver cannot obtain an optimal solution within 1 h when the planning-time horizon is greater than 120 min. With the rolling-time horizon approach, the rescheduled timetable can be obtained within 124 s for the 300 min planning-time horizon using 180 min rolling-time window.

Train dispatching (TD) is at the forefront of all rail operations that transport passengers or goods. Recent technological advances and the explosion of digital data have introduced data-driven methods (DDMs) in rail operations. In this study, DDMs on the TD problem are briefly explored, focusing on relevant studies on delay distribution, delay propagation, and timetable rescheduling. Data-driven TD methods, including statistical methods (SM), graphical models (GM), and machine learning (ML) methods are reviewed. Then, key issues in establishing different data-driven models for the TD problem are addressed. Subsequently, ML methods are considered to be among the most promising DDMs that lead to innovative TD methods, relying on rich data obtained from train operations. This study emphasizes the potentials for designing new alternatives in the three key fields of interest and provides directions for further research on TD. Future research, including the ML-driven TD and intelligent TD, were discussed in this study.

The propose of this paper is building the flow shop model with full-loaded constraints and maximum wagons within the stage. Based on sequence theory, technical operations of marshalling station are described as process of flow shop. By definition of key trains, the adjustment of the classification schedule of inbound trains is attributed to the adjustment of key trains for reducing invalid solution. Based on the LS rules to construct an initial solution, tabu search algorithm (TS) dynamically adjusts taboo step, and build a network model of static wagon-flow allocation for the objective function, to ensure the feasibility of solutions. Finally, the example demonstrates the effectiveness of the algorithm, and differences between full-loaded and full-cars constrains. [ABSTRACT FROM AUTHOR]

The paper aims to provide an overview of the key factors to consider when performing reliable modelling of rail services. Given our underlying belief that to build a robust simulation environment a rail service cannot be considered an isolated system, also the connected systems, which influence and, in turn, are influenced by such services, must be properly modelled. For this purpose, an extensive overview of the rail simulation and optimisation models proposed in the literature is first provided. Rail simulation models are classified according to the level of detail implemented (microscopic, mesoscopic and macroscopic), the variables involved (deterministic and stochastic) and the processing techniques adopted (synchronous and asynchronous). By contrast, within rail optimisation models, both planning (timetabling) and management (rescheduling) phases are discussed. The main issues concerning the interaction of rail services with travel demand flows and the energy domain are also described. Finally, in an attempt to provide a comprehensive framework an overview of the main metaheuristic resolution techniques used in the planning and management phases is shown. [ABSTRACT FROM AUTHOR]

The boarding/alighting process at railway platforms is an important determinant of the railway system performance and depends on the characteristics of passengers, the layout of the platform, and the rolling stock. This research aims to increase the understanding of the process, providing a methodological approach to model the passengers’ behaviour when boarding at railway platforms. Adequate criteria were selected to define the so called “boarding cluster” and an easy mechanism was developed to select the boarding clusters. Passenger flow data collected at Bern railway station in Switzerland was used to test the proposed approach. The results show that (a) the clusters near the doors grow in the longitudinal direction with a rate of 6:1 between the length and width of clusters, and that (b) the growth curves rise quickly when clusters are still small, i.e., at the beginning of the boarding/alighting activity. Further research is needed to extend the validation of the model, considering other variables, such as critical pedestrian densities which occur at specific hot spots near obstacles at platforms. [ABSTRACT FROM AUTHOR]

This paper addresses a real-life problem arising in the ongoing “Grand Paris” project. We investigate an environment-friendly urban freight transportation alternative using passenger rail network, by providing a decision support tool for decision makers to assess the technical feasibility, the impact on services to passengers, the needs in infrastructure and hence in investment. We identify relevant scientific issues that need to be addressed in this topic at strategical, tactical and operational levels. Then we focus on the Freight-Rail-Transport-Scheduling Problem which provides valuable information to and constitutes a basis for other related problems. This problem is first formulated into a MIP. We prove its NP-hardness and hence propose a heuristic based on dispatching rules and a single-train-based decomposition heuristic. The performances of these heuristics are evaluated via employing a discrete-event simulation approach, which also provides a general framework which supports decision-makers in modelling and evaluating the dynamics of such a system for various alternative solutions under various scenarios. [ABSTRACT FROM AUTHOR]

In a railway system, a conflict occurs when two trains require the same part of the infrastructure at the same time. Currently, such conflicts are typically resolved manually by experienced dispatchers. However, it is impossible for them to fully anticipate the impact of their actions on the entire network. This paper proposes a conflict prevention strategy which focuses only on the relevant part of the network and traffic and, consequently, proposes a solution for that part only. The proposed strategy first looks for possible rerouting options by using an optimization model. If no solution is found, a solution based on delaying one of the trains is required. This retiming/reordering heuristic uses information from an offline calculation, for determining related conflicts that frequently occur. In this way, a so-called dynamic impact zone is created online for each conflict. When deciding which train to delay, the potential conflicts and the incurred delays of all trains in this dynamic impact zone are taken into account. The performance of this new Conflict Prevention Strategy is compared to a common dispatching strategy, other heuristics, and an exact method. Extensive experiments on a large part of the Belgian railway network show that by considering this dynamic impact zone the total delay can be decreased by at least 67% compared to the basic First Come, First Served decision rule. Moreover, the dynamic impact zone has a reasonable size and scales well to large networks as only the relevant conflicts and their expected consequences are considered. This makes our Dynamic Impact Zone heuristic very fast. The computation time for returning a resolution to a conflict with the proposed conflict prevention strategy is, for 95% of the conflicts, less than two seconds, and at most 26 s, including the creation of the dynamic impact zone of the conflict. [ABSTRACT FROM AUTHOR]

Simulation methods are widely used in the field of railway planning and operations. Currently, several commercial software tools are available that not only provide functionality for railway simulation but also enable further evaluation and optimisation of the network for scheduling, dispatching, and capacity research. However, the various tools are all lacking with respect to the standards they utilise as well as their published interfaces. For an end-user, the basic mechanism and the assumptions built into a simulation tool are unknown, which means that the true potential of these software tools is limited. One of the most critical issues is the lack of the ability of users to define a sophisticated workflow, integrated in several rounds of simulation with adjustable parameters and settings. This paper develops and describes a user-based, customisable platform. As the preconditions of the platform, the design aspects for modelling the components of a railway system and building the workflow of railway simulation are elaborated in detail. Based on the model and the workflow, an integrated simulation platform with open interfaces is developed. Users and researchers gain the ability to rapidly develop their own algorithms, supported by the tailored simulation process in a flexible manner. The productivity of using simulation tools for further evaluation and optimisation will be significantly improved through the user-adaptable open interfaces. [ABSTRACT FROM AUTHOR]

General Electric Company (GE) partnered with Norfolk Southern Railroad (NS) to create and implement an optimization algorithm-based software system that dispatches thousands of trains in real time, increases their average speed, and allows NS to realize annual savings in the hundreds of millions of dollars. NS handles a range of rail traffic that includes intermodal, automobile transport, manifest freight, and passenger, all with unique priorities and scheduling requirements. Previously, dispatching for each geographic area was managed manually from regional dispatch centers and did not encompass a view of the entire rail network. The algorithm that we developed incorporates data about the properties of the rail networks (e.g., track layout, speed restrictions, height and weight restrictions), data about the trains (e.g., schedules, operating costs, train characteristics), and additional activities associated with train dispatching, such as crew changes and inspections. In doing so, we created a novel system to manage all train dispatching, increased the average speed of trains by two miles per hour, and decreased operating costs, while significantly improving schedule adherence and crew expirations. Every mile-perhour increase in average speed translates to $200 million savings in capital and operational expenses annually for NS. GE is currently implementing this system at two other railroads and is gaining additional important benefits from the project. [ABSTRACT FROM AUTHOR]

To improve the service quality of the railway system (e.g., punctuality and travel times) and to enhance the robust timetabling methods further, this paper proposes an integrated two-stage approach to consider the recovery-to-optimality robustness into the optimized timetable design without predefined structure information (defined as flexible structure) such as initial departure times, overtaking stations, train order and buffer time. The first-stage timetabling model performs an iterative adjustment of all departure and arrival times to generate an optimal timetable with balanced efficiency and recovery-to-optimality robustness. The second-stage dispatching model evaluates the recovery-to-optimality robustness by simulating how each timetable generated from the first-stage could recover under a set of restricted scenarios of disturbances using the proposed dispatching algorithm. The concept of recovery-to-optimality is examined carefully for each timetable by selecting a set of optimally refined dispatching schedules with minimum recovery cost under each scenario of disturbance. The robustness evaluation process enables an updating of the timetable by using the generated dispatching schedules. Case studies were conducted in a railway corridor as a special case of a simple railway network to verify the effectiveness of the proposed approach. The results show that the proposed approach can effectively attain a good trade-off between the timetable efficiency and obtainable robustness for practical applications. [ABSTRACT FROM AUTHOR]

We consider the real-time resolution of conflicts arising in real-world train management applications. In particular, given a nominal timetable for a set of trains and a set of modifications due to delays or other resources unavailability, we are aiming at defining a set of actions which must be implemented to grant safety, e.g., to avoid potential conflicts such as train collisions or headway violations, and restore quality by reducing the delays. To be compatible with real-time management, the required actions must be determined in a few seconds, hence specialized fast heuristics must be used. We propose a fast and effective parallel algorithm that is based on an iterated greedy scheduling of trains on a time-space network. The algorithm uses several sortings to define the initial train dispatching rule and different shaking methods between iterations. The performance is further enhanced by using various sparsification methods for the time-space network. The best algorithm configuration is determined through extensive experiments, conducted on a set of instances derived from real-world networks and instances from the literature. The resulting heuristic proved able to consistently resolve the existing conflicts and obtaining excellent solution quality within just two seconds of computing time on a standard personal computer, for instances involving up to 151 trains and two hours of planning time horizon. [ABSTRACT FROM AUTHOR]

In view of the complexity and timeliness of train operation plan adjustment, a new algorithm of revolvingly calling ant colony algorithm is proposed in this paper. This new algorithm is proposed in consideration of train dispatching command process based on ant colony algorithm and is proposed based on the shortest path analysis of trains in emergency according to the idea that many shortest paths should be found for train operation path. With the (k-1) shortest path found, this algorithm can be used to search the K-th shortest path to solve or mitigate the problem of reasonable path allocation in adjustment of train operation plan and avoid the lack of passing capacity in local sections. [ABSTRACT FROM AUTHOR]

Train dispatching is vital for the punctuality of train services, which is critical for a train operating company (TOC) to maintain its competitiveness. Due to the introduction of competition in the railway transport market, the issue of discrimination is attracting more and more attention. This paper focuses on delivering non-discriminatory train dispatching solutions while multiple TOCs are competing in a rail transport market, and investigating impacting factors of the inequity of train dispatching solutions. A mixed integer linear programming (MILP) model is first proposed, in which the inequity of competitors (i.e., trains and TOCs) is formalized by a set of constraints. In order to provide a more flexible framework, a model is further reformulated where the inequity of competitors is formalized as the maximum individual deviation of competitors’ delay cost from average delay cost in the objective function. Complex infrastructure capacity constraints are considered and modelled through a big M -based approach. The proposed models are solved by a standard MILP solver. A set of comprehensive experiments is conducted on a real-world dataset adapted from the Dutch railway network to test the efficiency, effectiveness, and applicability of the proposed models, as well as determine the trade-off between train delays and delay equity. [ABSTRACT FROM AUTHOR]

We introduce the decision support tool PANDA ( Passenger Aware Novel Dispatching Assistance). Our web-based tool is designed to provide train dispatchers with detailed real-time information about the current passenger flow and the multi-dimensional impact of waiting decisions in case of train delays. After presenting the algorithmic background and PANDA's main features, we show how it can be utilized in a typical use case scenario for train dispatchers. Besides its practical value for train dispatchers, the framework can be used to systematically study scientific questions. Exemplarily, we use our software to experimentally analyse the influence of waiting decisions on realistic passenger flows of Deutsche Bahn. In a first experiment, we evaluate PANDA's potential benefit for passengers. Our findings indicate that a remarkable reduction in total delay might be possible in comparison to current practice. In two additional experiments, we investigate the timing aspect of waiting decisions. Our observations suggest that the timing of waiting decisions is of crucial importance and that a carefully implemented early rerouting strategy has a significant potential to reduce resulting delays of passengers. [ABSTRACT FROM AUTHOR]

As train passengers expect a high degree of reliability from a railway network with minimal delays, during the timetabling process planners need to balance the goals of maximizing the offered capacity and delay resistance. This is often done in a two-step process where first a feasible timetable is found for a given line structure, and consecutively the stability of this timetable is evaluated and local modifications are performed to the timetable. This paper describes an optimization method to find a feasible periodic timetable that also ensures maximum stability for heterogeneous railway networks. The model is capable to handle flexible train orders, running and dwell times, and overtaking locations. We use the minimum cycle time of the periodic timetable as an indicator for stability, and define an optimization problem with this minimum cycle time as the objective function to be minimized. We also present dimension reduction methods and an iterative optimization approach to improve the mathematical optimization process. We show the applicability of the approach with case studies on the central part of the Dutch railway network. [ABSTRACT FROM AUTHOR]

Transit systems in which buses or trains always visit each and every stop along corridors are compared against those that feature two alternative vehicle-dispatching schemes. The alternatives entail so-called skip-stop and express/local services. Continuous models found in the literature are expanded so that the alternatives could be compared under a wider array of options. Comparisons are separately drawn for systems that feature buses, BRT and metro-rail trains, both for cities that are wealthy and for those that are not. Idealizations in regard to travel demand and route symmetry are assumed in pursuit of insights useful for high-level planning. Two rounds of parametric comparisons are conducted. In the first round, optimally-designed all-stop systems are presumably converted to furnish instead the alternative strategies without altering the original stop locations. In the second round, alternative schemes are designed in fully-optimized fashion from scratch. In both rounds, alternative dispatching schemes often bring lower generalized costs than do their optimally-designed all-stop counterparts. Estimated savings can reach 10% even in the first round where the alternative schemes are hampered by sub-optimal stop locations. If designed from scratch, the savings can reach 30%. Skip-stop service is found most often to be the lowest-cost option of the three. [ABSTRACT FROM AUTHOR]

Advanced decision support for rail traffic control is significant for enhancing the safety and quality of railway transport service. Data-driven methods have shown powerful learning ability and wide extensibility for prediction, classification, and decision-making problems. In this paper, we propose a hybrid prediction model based on deep forest (DF) ensemble learning to analyze the two common rail traffic control actions, i.e., changing the dwelling times and running times. This basic concept is to mimic the decision-making of rail traffic controllers, providing them with advanced decisions/control actions using data-driven learning algorithms. According to the decision-making approach of rail traffic controllers, the learning process of the model is split into two stages, i.e., learning the type of action (ToA) and the number of changes (NoC) in the dwelling times and running times (i.e., how many dwelling times or running times have been changed compared with the planned ones). The first stage is a classification problem; thus, DF classifier with the synthetic minority oversampling technique (SMOTE) is employed to deal with imbalanced data. In the second stage, the DF regressor treats the NoC in the dwelling and running times as numerical variables and utilizes the information from stage one, i.e., the prediction results of the classification model, to make predictions. The proposed model is calibrated on train operation data from two high-speed railway lines in China. The experimental results and comparative analyses show that the proposed method provides advanced and timely decision support for controllers. These characteristics of the proposed model are imperative for supporting the dynamic decision-making of controllers to manage railway traffic. [ABSTRACT FROM AUTHOR]

This paper presents an analytical–synthetic model of ergonomic research of the abilities of the dispatcher/operator in the control room for the automatic control of railway transportation. Twenty performance indicators describing the operators’ performance (work capacity and perceptive abilities) and the main characteristics of the control room (work organization and ergo-technical analysis) are identified. A group fuzzy analytic hierarchy process is applied in the process of ranking and selection of key performance indicators of railway control rooms. The selected key performance indicators (the operator’s hand movement, visual symptoms of fatigue, device error analysis, location and dimensions of the control desk) are analysed in detail. [ABSTRACT FROM AUTHOR]

After major capacity breakdown(s) on a railway network, train dispatchers need to generate appropriate dispatching plans to recover the impacted train schedule from perturbations and minimize the expected total train delay time under stochastic scenarios. In this paper, we propose a cumulative flow variables-based integer programming model for dispatching trains under a stochastic environment on a general railway network. Stable Train Routing (STR) constraints are introduced to ensure that trains traverse on the same route across different capacity breakdown scenarios, which are further reformulated to equivalent linear inequality constraints. Track occupancy and safety headways are modelled as side constraints which are dualized through a proposed Lagrangian relaxation solution framework. The original complex train dispatching problem is then decomposed to a set of single-train and single-scenario optimization subproblems. For each subproblem, a standard label correcting algorithm is embedded for finding the time dependent least cost path on a space-time network. The resulting dual solutions can be transformed to feasible solutions through priority rules. Numerical experiments are conducted to demonstrate the efficiency and effectiveness of the proposed solution approach. [ABSTRACT FROM AUTHOR]

Train movements on railway lines are generally controlled by human dispatchers. Because disruptions often occur, dispatchers make real-time scheduling and routing decisions in an attempt to minimize deviations from the official timetable. This optimization problem is called train dispatching. We represent it as a mixed integer linear programming model, and solve it with a Benders'-like decomposition within a suitable master/slave scheme. Interestingly, the master and the slave problems correspond to a macroscopic and microscopic representation of the railway, recently exploited in heuristic approaches to the problem. The decomposition, along with some new modeling ideas, allowed us to solve real-life instances of practical interest to optimality. Automatic dispatching systems based on our macro/micro decomposition-in which both master and slave are solved heuristically-have been in operation in several Italian lines since 2011. The exact approach described in this paper outperforms such systems on our test bed of real-life instances. Furthermore, a system based on another version of the exact decomposition approach has been in operation since February 2014 on a line in Norway. [ABSTRACT FROM AUTHOR]

The article focuses on evaluation of human reliability in the human - machine system in the railway industry. Based on a survey of a train dispatcher and of selected activities, we have identified risk factors affecting the dispatcher's work and the evaluated risk level of their influence on the reliability and safety of preformed activities. The research took place at the authors' work place between 2012-2013. A survey method was used. With its help, authors were able to identify selected work activities of train dispatcher's risk factors that affect his/her work and the evaluated seriousness of its influence on the reliability and safety of performed activities. Amongst the most important finding fall expressions of unclear and complicated internal regulations and work processes, a feeling of being overworked, fear for one's safety at small, insufficiently protected stations. [ABSTRACT FROM AUTHOR]

The paper presents a new urban public traffic supernetwork model by using the existing bus network modeling method, consisting of the conventional bus traffic network and the urban rail traffic network. We investigate the synchronization problem of urban public traffic supernetwork model by using the coupled complex network’s outer synchronization theory. Analytical and numerical simulations are given to illustrate the impact of traffic dispatching frequency and traffic lines optimization to the urban public traffic supernetwork balance. [ABSTRACT FROM AUTHOR]

Optimal alternative selection to address the emergency situation is critical for dispatcher group in Unattended Train Operation (UTO) to guide emergency process. It is difficult to provide the precise decision value under one criterion and to evaluate the emergency alternatives among multiple dispatchers. This paper presents a hybrid emergency decision-making method integrating fuzzy analytic hierarchy process (FAHP) described by linguistic terms with enhanced weighted ordered weighted averaging (WOWA) operator. The enhanced WOWA operator aggregates the preference matrices of multidispatcher through the constructed emergency response task model of dispatcher group in OCC. This calculation approach takes into consideration the relations of emergency tasks to derive the importance weights of dispatchers and integrates them into the ordered weighted averaging (OWA) operator weights based on a fuzzy membership relation. A case study of applying the method in an emergency of a train fire is given to demonstrate the feasibility and usefulness of the methods associated with the group multicriteria decision-making (GMCDM) theory in emergency management of UTO metro system. [ABSTRACT FROM AUTHOR]

To further improve the utilization rate of railway tracks and reduce train delays, this paper focuses on developing a high-efficiency train routing and timetabling approach for double-track railway corridors in condition that trains are allowable to travel on reverse direction tracks. We first design an improved switchable policy which is rooted in the approaches by Mu and Dessouky (2013), with the analysis of possible delays caused by different path choices. Then, three novel integrated train routing and timetabling approaches are proposed on the basis of a discrete event model and different dispatching rules, including no switchable policy (No-SP), Mu and Dessouky (2013)’s switchable policy (Original-SP) and improved switchable policy (Improved-SP). To demonstrate the performance of the proposed approaches, the heterogeneous trains on Beijing–Shanghai high speed railway are scheduled by aforementioned approaches. The case studies indicate that in comparison to No-SP and Original-SP approaches, respectively, the Improved-SP approach can reduce the total delay of trains up to 44.44% and 73.53% within a short computational time. Moreover, all of the performance criteria of the Improved-SP approach are usually better than those of other two approaches. [ABSTRACT FROM AUTHOR]

The technology for controlling the distance between two trains is shifting from traditional fixed red, yellow and green signals on the infrastructure track circuits towards more and more dynamic systems, which are based on moving blocks, where the distance is computed according to real-time positioning, and the control of the distance is computed on-line. This is the case, for example, in the European Rail Traffic Management System (ERTMS), which proposes three different levels, from 1 to 3. This paper addresses the time-honoured problem of scheduling trains on a single track, in the light of recent results in robust team decision theory. The control model can be used in two modes: as a decision support tool for train dispatchers to evaluate the distance between trains in the current schedule, and as a planning tool to evaluate the effects of timetable changes. The main contribution of the paper is the application of a recent result in robust team decision theory to control noncritical train distances in moving blocks, such as in ERTMS Level 3. The case study is related to real data from an ERTMS simulation and controller software tool. [ABSTRACT FROM AUTHOR]

Trains' movements on a railway network are regulated by official timetables. Deviations and delays occur quite often in practice, demanding fast rescheduling and rerouting decisions in order to avoid conflicts and minimize overall delay. This is the real-time train dispatching problem. In contrast with the classic "holistic" approach, we show how to decompose the problem into smaller subproblems associated with the line and the stations. This decomposition is the basis for a master-slave solution algorithm, in which the master problem is associated with the line and the slave problem is associated with the stations. The two subproblems are modeled as mixed integer linear programs, with specific sets of variables and constraints. Similarly to the classical Benders' decomposition approach, slave and master communicate through suitable feasibility cuts in the variables of the master. Extensive tests on real-life instances from single and double-track lines in Italy showed significant improvements over current dispatching performances. A decision support system based on this exact approach has been in operation in Norway since February 2014 and represents one of the first operative applications of mathematical optimization to train dispatching. [ABSTRACT FROM AUTHOR]

Identifying the traffic dispatcher error behaviors that frequently result in the occurrence of metro accidents is beneficial to prevent error behaviors and mitigate their consequences. Yet, there is no theoretical framework available for metro safety officers in investigating and classifying traffic dispatcher error behaviors. This article presents a structured procedure to analyze traffic dispatcher error behaviors in emergency based on the human information processing theory and the modified task analysis framework. In order to make the proposed method be more applicable to practical use, a detailed task list of traffic dispatcher in case of emergency is given by considering the characteristic of equipment in operation control center (OCC) to simplify the task analysis procedure. And the traffic dispatcher error behavior classification with an error degree value scale derived from the VACP model is built to identify the error behavior type, which defined human behaviors according to the information processing stages. Finally, the validation and reliability studies have been carried out to assess the reasonability of the proposed method. The grey relational analysis (GRA) of the data from 98 traffic dispatcher error related accident reports indicates an acceptable validation of the proposed error behavior classification. And the reliability analysis suggests an adequate inter-coder consensus of more than 70% percentage agreement of the proposed method in practical use. [ABSTRACT FROM AUTHOR]

The high-speed railway dispatching command system is the nerve center of a high-speed railway. The construction of such a system that has high reliability is of great significance in ensuring the safe operation and all-weather operation of trains. This study analyses the collaborative needs of a high-speed railway dispatching system, and investigates the organizational coordination of the system in terms of a collaborative plan, organizational coordination, information coordination, etc. The coordination mechanism of a high-speed railway dispatching command system should be based on three perspectives: (1) The vertical hierarchical level of the high-speed railway dispatching system's coordination, (2) The primary and auxiliary synergies of the horizontal professional subsystem, and (3) The cooperation between dispatching stations, as well as between the high-speed railway and the existing line command system. In this paper, we propose a theory of coordination between a high-speed railway dispatching command system and the existing lines, as well as a method for its implementation. Together, this theory and method will provide theoretical guidance and technical support in the development of a dispatching command system. [ABSTRACT FROM AUTHOR]

Train dispatching is critical for the punctuality and reliability of rail operations, especially for a complex rail network. This paper develops an innovative integer programming model for the problem of train dispatching on an N-track network by means of simultaneously rerouting and rescheduling trains. Based on a time-space network modeling framework, we first adapt a commonly used big-M method to represent complex "if-then" conditions for train safety headways in a multi-track context. The track occupancy consideration on typical single and double tracks is then reformulated using a vector of cumulative flow variables. This new reformulation technique can provide an efficient decomposition mechanism through modeling track capacities as side constraints which are further dualized through a proposed Lagrangian relaxation solution framework. We further decompose the original complex rerouting and rescheduling problem into a sequence of single train optimization subproblems. For each subproblem, a standard label correcting algorithm is embedded for finding the time dependent least cost path on a time-space network. The resulting dual solutions can be transformed to feasible solutions through priority rules. We present a set of numerical experiments to demonstrate the system-wide performance benefits of simultaneous train rerouting and rescheduling, compared to commonly-used sequential train rerouting and rescheduling approaches. [ABSTRACT FROM AUTHOR]

Highlights: [•] Stability of railway rescheduling plans is analysed under a stochastic environment. [•] A dispatching tool is integrated in a closed-loop with a railway traffic simulator. [•] Rescheduling plans become unstable when disturbances start propagating. [•] Train reordering varies more when enlarging the length of the prediction horizon. [•] Longer prediction horizons lead to solutions that prefer reordering to retiming. [Copyright &y& Elsevier]

Purpose: The train dispatching is a crucial issue in the train operation adjustment when passenger flow outbursts. During holidays, the train dispatching is to meet passenger demand to the greatest extent, and ensure safety, speediness and punctuality of the train operation. In this paper, a fuzzy passenger demand forecasting model is put up, then a train dispatching optimization model is established based on passenger demand so as to evacuate stranded passengers effectively during holidays. Design/methodology/approach: First, the complex features and regularity of passenger flow during holidays are analyzed, and then a fuzzy passenger demand forecasting model is put forward based on the fuzzy set theory and time series theory. Next, the bi-objective of the train dispatching optimization model is to minimize the total operation cost of the train dispatching and unserved passenger volume during holidays. Finally, the validity of this model is illustrated with a case concerned with the Beijing-Shanghai high-speed railway in China. Findings: The case study shows that the fuzzy passenger demand forecasting model can predict outcomes more precisely than ARIMA model. Thus train dispatching optimization plan proves that a small number of trains are able to serve unserved passengers reasonably and effectively. Originality/value: On the basis of the passenger demand predictive values, the train dispatching optimization model is established, which enables train dispatching to meet passenger demand in condition that passenger flow outbursts, so as to maximize passenger demand by offering the optimal operation plan. [ABSTRACT FROM AUTHOR]

Abstract: Train re-scheduling problems are popular among researchers who have interest in the railway planning and operations fields. Deviations from normal operation may cause inter-train conflicts which have to be detected and timely resolved. Except for very few applications, these tasks are usually performed by train dispatchers. Due to the complexity of re-scheduling problems, dispatchers utilize some simplifying rules to resolve conflicts and implement their decisions accordingly. From the system effectiveness and efficiency point of view, their decisions should be supported with appropriate tools because their immediate decisions may cause considerable train delays in future interferences. Such a decision support tool should be able to predict overall implications of the alternative solutions. Genetic algorithms (GAs) for conflict resolutions were developed and evaluated against the dispatchers’ and the exact solutions. The comparison measures are the computation time and total (weighted) delay due to conflict resolutions. For benchmarking purposes, artificial neural networks (ANNs) were developed to mimic the decision behavior of train dispatchers so as to reproduce their conflict resolutions. The ANN was trained and tested with data extracted from conflict resolutions in actual train operations in Turkish State Railways. The GA developed was able to find the optimal solutions for small sized problems in short times, and to reduce total delay times by around half in comparison to the ANN (i.e., train dispatchers). [Copyright &y& Elsevier]

Abstract: An important problem in management of railway systems is the train scheduling/timetabling problem. This is the problem of determining a timetable for a set of trains that do not violate track capacities and satisfy some operational constraints. In this study, a feasible timetable generator framework for stochastic simulation modelling is developed. The objective is to obtain a feasible train timetable for all trains in the system. The feasible train timetable includes train arrival and departure times at all visited stations and calculated average train travel time. Although this study focuses on train scheduling/timetabling problem, the developed simulation framework can also be used for train rescheduling/dispatching problem if this framework can be fed by real time data. The developed simulation model includes stochastic events, and can easily cope with the disturbances that occur in the railway system. [Copyright &y& Elsevier]

Abstract: During real-time traffic management, the railway system suffers perturbations. The task of dispatchers is to monitor traffic flow and to compute feasible rescheduling solutions in case of perturbed operations. The main objective of the infrastructure manager is delay minimization, but the dispatchers also need to comply with the objectives of the train operating companies. This paper presents an innovative optimization framework in order to reschedule trains with different classes of priority, that can be computed statically or dynamically in order to include the needs of different stakeholders. An iterative train scheduling procedure is proposed in order to compute feasible train schedules for an ordered set of priority classes, from the highest one to the lowest one. At each step, the procedure focuses on the current priority class, preserving solution quality from the higher priority classes and neglecting lower priority classes in the optimization of train orders and times. The multi-class rescheduling problem is formulated via alternative graphs that are able to model precisely train movements at the microscopic level of block sections and block signals. Each step of the iterative train scheduling procedure is solved to optimality by a state-of-the-art branch and bound algorithm. The results show an interesting gap between single-class and multi-class rescheduling problems in terms of delay minimization. Each priority class is also evaluated in order to assess the performance of the different rescheduling solutions. [Copyright &y& Elsevier]

Efficiently coordinating the movement of trains on a railway network is a central part of the planning process for a railway company. This paper reviews models and methods that have been proposed in the literature to assist planners in finding train routes. Since the problem of routing trains on a railway network entails allocating the track capacity of the network (or part thereof) over time in a conflict-free manner, all studies that model railway track allocation in some capacity are considered relevant. We hence survey work on the train timetabling, train dispatching, train platforming, and train routing problems, group them by railway network type, and discuss track allocation from a strategic, tactical, and operational level. [ABSTRACT FROM AUTHOR]

The mechanism of train operation conflict based of the definition of train operation conflict for high-speed railways was analized. The conflicts are classified from 3 aspects. A review of research history and the study actuality of train operation conflict management in China and abroad after consulting or reading a lot of literature and research reports. And the analysis shows that the studies on train operation conflict management are carried out mainly relying on railway diagram optimization and dispatching system development in China and abroad. There are few of special and systematic jobs about this problem and there is no conflict management system that is suitable for high-speed railways under the conditions of China. Conflict analysis, conflict resolution, train operation adjustment method and operation plan optimization based on conflict management are the main contents of train operation conflict management for high-speed railways in China. Time-varying, transmissible, separated management and complexity are the important characteristics of conflict management for high-speed railways. [ABSTRACT FROM AUTHOR]

Abstract: After a major service disruption on a single-track rail line, dispatchers need to generate a series of train meet-pass plans at different decision times of the rescheduling stage. The task is to recover the impacted train schedule from the current and future disturbances and minimize the expected additional delay under different forecasted operational conditions. Based on a stochastic programming with recourse framework, this paper incorporates different probabilistic scenarios in the rolling horizon decision process to recognize (1) the input data uncertainty associated with predicted segment running times and segment recovery times and (2) the possibilities of rescheduling decisions after receiving status updates. The proposed model periodically optimizes schedules for a relatively long rolling horizon, while selecting and disseminating a robust meet-pass plan for every roll period. A multi-layer branching solution procedure is developed to systematically generate and select meet-pass plans under different stochastic scenarios. Illustrative examples and numerical experiments are used to demonstrate the importance of robust disruption handling under a dynamic and stochastic environment. In terms of expected total train delay time, our experimental results show that the robust solutions are better than the expected value-based solutions by a range of 10–30%. [Copyright &y& Elsevier]

Railway traffic experiences disturbances during operations that cause conflicts between train paths or even deadlock situations. Dispatchers need actions to restore feasibility and limit spreading of delays through the network. To help them in such a task, the dispatching support tool ROMA (Railway traffic Optimization by Means of Alternative graphs) has been implemented in a laboratory environment. This paper reports on enhancements to the underlying train dispatching model as well as to the solution algorithms studied in order to tackle the increased complexity of busy stations with multiple conflicting paths and high service frequencies. Advanced train reordering and rerouting techniques are compared with straightforward rules and the current approach in the Netherlands. Extensive computational studies based on accepted statistical distributions of train delays for Utrecht Central Station assess the effectiveness of the ROMA tool in terms of solution quality and computation time. [ABSTRACT FROM AUTHOR]

Abstract: Wagon fleet is an essential component of the railways business. Motivated by the recent concern on freight wagon management in Europe and based on the experience from the deployment and pilot demonstrations of an advanced wagon management system in Europe, the current work presents main technological and organizational issues associated with a wagon pool, created and used by a railway operator partnership. The results include the identification of the essential hardware and software requirements for the implementation of such a system (user/wagon reservation, track-and-trace and energy-saver equipment, loading/unloading sensors, wagon dispatching and delay management functionalities) as well as the outcome of the investigation of significant organizational aspects of the system (imbalance between wagon offer and wagon demand, fair allocation of benefits among the users of the system, savings that can be achieved thanks to estimated time of arrival information, consideration of reliability metrics into the optimal empty wagons allocation problem). [Copyright &y& Elsevier]

Abstract: Railway traffic control by dispatchers in case of abnormality is critical to assure the service quality of a railway system’s operation. However, this unique professional knowledge often lies in the dispatcher’s mind. Therefore, this study aims to transform a train dispatcher’s expertise into a useful knowledge rule. The fuzzy Petri Net approach is adopted to formulate the decision rules of train dispatchers in case of abnormality as the basis for future development of a dispatching decision support system. The dispatching decision rules, factors, and possible options when perturbation happens are collected via expert interviews and literature reviews. This study discusses the abnormal scenarios, including centralized traffic control system failure, automatic train protection failure, and locomotive failure. A case study of a line section of Taiwan’s railway network is implemented and the empirical result could be used as a reference in railway dispatching in case of abnormality. [Copyright &y& Elsevier]

Incidents and waiting for train connections are registered by dispatchers as sources of train delays, but route and headway conflicts are not always clearly recognized. Moreover, traffic management and route setting are the primary task of dispatchers and signallers, whilst monitoring and incident registration is not allowed to take up too much of their time. This paper describes a tool that automatically and without discrimination identifies route conflicts and the train numbers involved. It is based on standard train describer and infrastructure messages recorded on the Dutch railway network. The logic of these messages is captured in a coloured Petri net (CPN) model on which a prototype tool for route conflict identification and estimation of knock-on delay has been developed. [ABSTRACT FROM AUTHOR]

We address the problem of generating detailed conflict-free railway schedules for given sets of train lines and frequencies. To solve this problem for large railway networks, we propose a network decomposition into condensation and compensation zones. Condensation zones contain main station areas, where capacity is limited and trains are required to travel with maximum speed. They are connected by compensation zones, where traffic is less dense and time reserves can be introduced for increasing stability. In this paper, we focus on the scheduling problem in condensation zones. To gain structure in the schedule we enforce a time discretisation which reduces the problem size considerably and also the cognitive load of the dispatchers. The problem is formulated as an independent set problem in a conflict graph, which is then solved using a fixed-point iteration heuristic. Results show that even large-scale problems with dense timetables and large topologies can be solved quickly. [ABSTRACT FROM AUTHOR]

Dispatching support systems are currently being researched, which try to find the optimal order of trains in conflict situations and thereby improve the efficiency of railway operation. Recently, some approaches are presented to further decrease delays by anticipating train control, i.e. slowing down a train before a possible conflict in order to avoid unscheduled stops and reduce their consequences (high delay, high energy consumption, low comfort for passengers). The proposed kind of speed regulation in conflict situations is presented as a consecutive step to train dispatching, although it modifies the objective function of the previous step (delay: objective function during dispatching). This paper analyses the consequences of this sequential approach and describes the circumstances under which the optimal solution of a conflict situation can not be found this way. It proposes the concept of “time losses” whose integration into dispatching algorithms promises better solutions. [ABSTRACT FROM AUTHOR]