ABSTRACT. In the operational management of railway networks, an important requirement is the fast adaptation of timetable scenarios, in which operational disruptions or time windows with temporary unavailability of infrastructure, for instance during maintenance time windows, are taken into consideration. In those situations, easy and fast reconfiguration and recalculation of timetable data is of central importance. This local and temporal rescheduling results in shifted departure and arrival times and sometimes even in modified stop patterns at intermediate stations of train runs. In order to generate reliable timetabling results it is a prerequisite that train-track assignments, as well as operational and commercial dependencies are taken into consideration. In order to refer to the right level of detail for modelling track infrastructure and train dynamics in the computer aided planning process we present a generic model that we call Track-Choice FPESP (TCFPESP), as it implements suitable extensions of the established PESP-model. We show, how the service intention (the data structure for timetable specification) together with resource capacity information entered into a standard timetabling tool like Viriato can be utilized in order to configure the TCFPESP model. In addition, we are able to calculate quantitative performance measures for assessing timetable quality aspects. In order to achieve this we present a method for evaluating travel times based on passenger routings and a method for evaluating timetable robustness based on max-plus algebra. This approach supports the planner to generate integrated periodic timetable solutions in iterative development cycles and taking into account intervals for local maintenance work.

ABSTRACT. It is critical to design train timetables in urban rail transit network that can not only meet the daily time-dependent passenger demand, but also meet the passenger demand with day-to-day variations as well as remain stable and regular in a long term. The existing studies are not deep enough in uncertain-demand network-level train timetabling problem. Furthermore, the most studies concentrated on the passengers’ cost and neglected the operation companies’ cost. This study proposes two mixed-integer linear multi-objective models under uncertain demand in rail transit network. The first one is on line level and the second one is on network level. Based on the perspective of both passengers and operation companies, the objective function is expressed as the weighted summation of average waiting time, final retention ratio and train services’ quantity. The uncertainty of train services quantity, the restriction of train services capacity and the transfer behaviour between lines are also taken into account. A scenario-based stochastic programing approach is applied to handle the models, which takes the passenger demand in a number of random selected days as a set of scenarios. A case study is presented to testify the effectiveness of the models and the efficiency of the approach. The results show a decline in general objectives during the multiple planning days. It suggests that the proposed models can keep balance between service quality and service cost in the long-term practice.

ABSTRACT. One of the criteria to judge a timetable is what passengers think of it, and an operator has to take this into account when designing a timetable. We study this problem in a case study from the Netherlands, where on part of the network the frequency of trains has increased recently. We formulate a model that integrates passenger routing and timetabling in order to find timetables that are good for passengers. This can be used for studies by railway operators, and by infrastructure managers to decide where to invest in new infrastructure.

ABSTRACT. Train crews are a considerable expense for North American freight railways. Unlike many railway operations in Europe and other countries, freight railways in the United States must operate mainline trains with two-person crews (engineer and conductor). Besides human factors and safety concerns, the need for two crew members to perform work events en route, such as serving mainline customers, presents an obstacle to reducing labour costs by adopting single-person crews. To overcome this obstacle, railroads have proposed to operate each train with a single-person crew and replace the on-board conductors with “roaming conductors” who travel in highway vehicles and assist different trains with work events. The objective of this study is to determine the feasibility of replacing conventional on-board conductors with roaming conductors by solving the problem of optimally assigning train work events to roaming conductors. Various routing and scheduling approaches are developed to minimize the number of roaming conductors for a given operating plan. The results of Monte Carlo simulations show that based on different performance standards and practical assumptions in model parameters, the total number of roaming conductors will be less than the number of on-board conductors required for two-person crews. Depending on the operating conditions, roaming conductors can facilitate a net decrease in operating personnel (and associated decrease in labour costs) while still executing all required freight train work events. The scheduling algorithms developed through this research can help railroad practitioners determine where roaming conductors may be a feasible alternative to two-person crews.

ABSTRACT. As the largest single source of freight rail revenue, intermodal transportation of shipping containers and highway trailers by rail currently accounts for over one half of the total carloads hauled by Class 1 railroads in North America. A growing demand for freight transportation, along with record levels of North American intermodal rail traffic, has strained the capacity of the intermodal terminals dedicated to transloading containers and trailers to and from the rail mode. Since intermodal terminal capital and operating costs are substantial and greatly influence the competitiveness of intermodal by rail relative to other modes, railroads desire to optimize the utilization and capacity of existing facilities before investing in new construction. Although intermodal terminal capacity depends on a number of interrelated factors, current approaches to estimate intermodal terminal capacity rely on a combination of practitioner experience, historical trends and a limited number of single-factor capacity relationships. To provide industry practitioners with a better understanding of intermodal terminal capacity, this research investigates relationships between various capacity factors and intermodal terminal characteristics via simulation. A simulation model of a domestic inland intermodal terminal is developed using AnyLogic® software and used to test different facility layouts and operating scenarios. Preliminary results suggest that additional factors and interactions not considered by current capacity approaches may constrain intermodal terminal capacity and create congestion during periods of peak demand. It is anticipated that the final results will provide practitioners with new relationships to better evaluate the capacity of existing and proposed intermodal terminals.

ABSTRACT. Multi-stage train classification is a complex marshalling procedure that could be applied for simultaneous multi-group train formation. Simultaneous train formation is capable of processing a large volume classification insensitive on the number of outbound trains. Through multi-stage classification, wagons are moved several times to achieve desired outbound train sequences. The main optimization issue refers to finding a balance between the number of sorting steps and the total number of wagon movements. The optimization of the classification schedule could be addressed at different levels of the yard planning hierarchy. In this paper we develop mathematical formulation and two different heuristic algorithms to support tactical decisions for the multi-stage train classification problem. The main optimization issue refers to the allocation of tracks for performing multi-stage train classification minimizing annual operating costs. In order to validate the mathematical formulation and evaluate the efficiency of the proposed optimization model, we conduct computational tests and case study experimentations based on infrastructural and operational conditions applied in Belgrade marshalling yard in Serbia.

ABSTRACT. Studies on the spatiotemporal distribution and duration characteristics of railway disruptions are very significant for the advanced prediction of disruption and development of real-time dispatch strategies. In this study, historical disruption records of some Chinese High-Speed Railways (HSRs) lines from 2014–2016 were used to investigate the distribution characteristics of railway disruptions. The spatiotemporal probability distribution of four railway lines were calculated and their hotspots (coordinates with high probabilities) and coldspots (coordinates with low probabilities) were revealed using heatmaps. Furthermore, all the disruptions were classified into seven clusters based on their causes, and statistical analysis was carried out on each cluster. In addition, three right-skewed distribution models, namely Log-normal, Weibull, and Gamma distributions, were used to fit the duration of each cluster to uncover its duration regularities. Finally, goodness-of-fit test was performed on the models using the Kolmogorov-Smirnov method, indicating that the duration of each classified disruption can be estimated using a Log-normal distribution function. The obtained spatiotemporal probabilities and duration time distribution models thus can be further applied into estimating the occurrence and duration of railway disruption in real-time dispatching to help dispatchers make advanced decisions.

ABSTRACT. In Swedish context, the value of delay is deemed equalling to the value of travel time reliability (VoR), which mostly derived from Stated Preference (SP) studies. According to our knowledge, there are several issues with the SP method for obtaining VoR, for example, its deficiency in harmonizing the stated choices with the actual choices. On the other hand, Revealed Preference (RP) data from ticket sales has its limit in socioeconomic information of travellers and scenario variation. This project aimed to use a RP method to estimate VoR from several selected railway corridors, with Bayesian posterior analysis to infer socioeconomic differences between passengers given on their actual choices.

The data in the study are from two sources, ticket sales data from a major passenger operator SJ, and data on train movements from Trafikverket’s (Swedish Transportation administration) TFÖR database. Both data sources are for the whole year 2009. The data includes 60 545 individual observations on traveler’s route choice for two specific trip relations. The chosen trip relations are long-distance non-commuting trips with travel distances between 200 and 250 kilometers.

The project is a “proof-of-concept” for possible use of ticket sales data for the estimation of VoR. We can conclude that the estimated VoR – 1,13 times value of travel time, is in compliance with results from previous international studies using SP and/or RP data. The simulated distribution of VoR from posterior analysis also clearly indicates a bimodal pattern of valuing travel reliability, probably due to socio-economic characteristics or trip purposes.

ABSTRACT. The paper analyses dwell time delays for commuter trains in Stockholm and Tokyo. In both cities, small dwell time delays of at most five minutes make up around 90% of the total delays. Therefore, it is valuable to understand and deal with these disturbances. To this end, we use high resolution data on dwell times and passenger counts from both countries over the last several years. We find that these data alone can explain about 40% of the variation in dwell time delays and produce simple models which can be used in practice to assign more appropriate dwell times. A change in the congestion rate of 10%, or 15 passengers per car, in Tokyo translates to a delay of about one second. For every 10 remaining passengers per car in Stockholm, the delay increases by about one second, and one boarding or alighting passenger per car corresponds to about 0.4 seconds of delay. We also find that trains in Tokyo are much more congested than in Sweden, and that at most stations in the latter, the exchange of passengers is quite small. In both cities, the range of dwell time delays is quite narrow, with between 40 and 50 seconds separating the 5th and 95th percentiles. This indicates further that most delays, by far, are very small, and that even small adjustments to dwell times can make a big difference in the overall picture. To facilitate such improvements, key stakeholders and practitioners are closely involved with the research.

ABSTRACT. The link between transport economics and railway operations analysis is unfortunately rather weak, even if there are notable exceptions of people and studies briding the gap. The aim of this keynote is therefore to illustrate how concepts and methods from transport economics can be useful for railway operations analysis, in particular analyses of capacity and regulations. I argue that the two fields have much to gain from a closer integration. I will do this by discussing three issues: a) timetable assumptions in cost-benefit analysis (CBA) of increased capacity, b) crowding costs in public transport CBA, and c) slot trading between operators in open-access railway markets.

ABSTRACT. In recent years, the environment of railways and the systems such as CBTC (Communication Based Train Control) have been changing. To respond the changes and the needs of customers, a unified train control system (UTCS) has been developed to realize a system that evolves with customers. Previous type systems consist of independent components such as ATC (Automatic Train Control) system, electronic interlocking system, and facility monitoring system, and there are a complicated overlap of system configurations and functions and difference in concept between the systems. On the other hand, the integrated train control system consists of horizontal layers such as function layer, network layer, and terminal layer. Therefore, the system has been developed to make it simple with no unnecessary redundancy and evolving to meet the needs of customers. In this paper, we explain a method that realizes the interlocking function in the function layer based on the concept of “securing a train travelling path” including path blocking and routing, and evaluate the safety of the method using STAMP/STPA.

ABSTRACT. As part of the smartrail 4.0 program, SBB is focusing with the project TMS (Traffic Management System) on algorithmic supported, optimized and integrated capacity planning. For solving this problem, we have experimented with different approaches from the literature and have compared their quality and performance for our specific instances. In this contribution, we present the results of this comparison and discuss how we want to use this for having the best possible solution for our ambitious goal.

ABSTRACT. Since railway companies have to apply for long-term public contracts to operate railway lines in public tenders, the question how they can estimate the operating cost for long-term periods adequately arises naturally. We consider a rolling stock rotation problem for a time period of ten years, which is based on a real world instance provided by an industry partner. We use a two stage approach for the cost estimation of the required rolling stock. In the first stage, we determine a weekly rotation plan. In the second stage, we roll out this weekly rotation plan for a longer time period and incorporate scheduled maintenance treatments. We present a heuristic approach and a mixed integer programming model to implement the process of the second stage. Finally, we discuss computational results for a real world tendering scenario.

ABSTRACT. Train-set is one of the most expensive assets of a railway system. Hence, the efficiency of train-set utilization is an important objective pursued in practice. An efficient train-set assignment plan, including the assignment of utilization paths and maintenance tasks, should be designed and implemented in accordance with demand (utilization schedule) and maintenance requirements. Previous studies have adopted the fixed periodic maintenance (PM) strategy for the train-set assignment problem. However, the difference in the reliability of train-set is not considered in this strategy. Maintenance planners have to manually adjust utilization and maintenance tasks on the basis of experience. This study proposes an optimization process for assigning train-set to utilization paths and maintenance tasks in accordance with the predictive maintenance strategy (PdM) with trainset-specific reliability models. Results of the empirical study demonstrate that the developed process with predictive maintenance can assign utilization paths and schedule maintenance tasks to each trainset efficiently and reduce the total cost by over 11% compared with the PM-only strategy. Adopting this process can help planners improve the efficiency and reliability of train-set utilization.

ABSTRACT. With a growing demand for metros in metropolises, such as London in the UK, network capacity should be ideally improved further. For metro lines with already high-frequency services, it is the train dwell time that determines the number of trains per hour in peak times. Passenger distribution on the platform affects the train dwell time, thereby the metro network capacity. This study has developed a model of passenger distribution on the metro platform. Not only are the layouts and congestion on the platform at the stations where passengers board the trains considered in the model, but also the passengers’ origin-destination pairs, the waiting time and the platform layouts at the stations where passengers alight. Loadweigh data (the weight of passengers in each train car), which is an economical alternative to the traditional manual counting, has been used to calibrate the model. The model is validated by the Chi-Square goodness of fit test and performs well to reflect the causes of passenger distribution on the platform. A case study of 8 stations on Hammersmith&City line of London Underground shows that there were on average 16% of passengers in the morning peak chose boarding cars on the platforms based on the locations of the platform exits or interchange passageways at the stations where they would alight. The results would be useful for the metro operation planners and station staff to take measures to manage passenger distribution on the platform.

ABSTRACT. This paper examines the extent to which delayed trains are also trains with more passengers. The paper uses unique passenger load data about regional trains in Sweden and combines this with Swedish delay statistics for the same train numbers and from the same time periods. Results show that trains with high passenger numbers are not delayed to a greater extent compared to trains with fewer passengers. Train punctuality is thus a good indicator of traveller punctuality in this case. These results also suggest that long boarding and alighting times due to high passenger numbers are not a main cause of delays, possible causes of delays are instead external factors such as track maintenance or dense train movements. Therefore, this result suggests that policy makers should look further into the latter causes. Furthermore, the paper also compares the share of travellers and trains that are more than half an hour late, i.e. that are significantly late. These differences are also small but larger than for the less delayed trains. For one of the railway lines, trains with high passenger loads are more than proportionally hit by long delays. Such cases suggest that train control priorities could be re-examined with more focus on improving the service for railway travellers.

ABSTRACT. The Hyperloop concept, pod competitions and actual development plans have recently attracted much publicity. The technologies of the most serious vacuum tube transport projects, Hyperloop by E. Musk (SpaceX) and Swissmetro by M. Jufer et al. (EPF Lausanne), are assessed with regard to their principal aims, system approaches and technical feasibility. The vehicle design, propulsion, levitation and practical capacity of the two (near) vacuum tube transport projects are compared with existing railway and Maglev trains. The potential high-speed long-distance travel demand is assessed for “Swissmetro” corridors in Europe and the proposed Hyperloop link Los Angeles- San Francisco in California, respectively. Major technical and environmental alignment and construction constraints for the design of the tubes, guideway and stations are identified. The consistency and safety of possible operating programs for the investigated corridors of Swissmetro and Hyperloop, are evaluated respectively. Finally, the main barriers and needs for further research and development are identified.

ABSTRACT. This study has led to the elaboration of a proposed methodology used to select and rank the most attractive corridors for the implementation of first commercial vacuum-tube train (or hyperloop) lines for passengers. From a list of the most populated cities all over the world, it has been possible to sort out the possible transport connections that could be travelled by hyperloop pods without having to build a tunnel or crossing a conflict area. Then, an evaluation of all selected corridors has been performed on the basis of defined classification criteria. Important parameters characterizing the potential of a corridor have been identified during the research: the number of air passengers on the corridor, the nature of the competitive transport infrastructure, the GDP per kilometre and the topography along the route. Some other minor criteria have also been used, in order to elaborate a robust tool which can be a good help for investors and decision makers. All selected corridors have been ranked, resulting in a short list of the 250 most attractive corridors for the implementation of first commercial lines. This study presents a proposal for the ranking of the most promising corridors. It should be followed by proper feasibility studies and ridership calculations.