297 research outputs found

    Development of a prototype for the automated generation of timetable scenarios specified by the transport service intention

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    Within the next 5 to 10 years, public transport in Switzerland as well as in other European countries will experience major technological and organisational changes. However, changes will also take place on the customer side, resulting in different mobility behaviour and demand patterns. These changes will lead to additional challenges for transport service providers in private as well as public domains. Time to market will be a key success factor and it is unnecessary to mention that due to these factors the speed and flexibility of business processes in freight as well as in passenger transport industry have to be increased significantly. Within the railway value chain (line planning, timetabling and vehicle scheduling etc.) the coordination of the individual planning steps is a key success factor. SBB as the leading service provider in public transport in Switzerland has recognized this challenge and, together with various partners, initiated the strategic project Smart Rail 4.0. The ZHAW and especially the Institute for Data Analysis and Process Design (IDP) of the School of Engineering wants to be part of this transformation process and to contribute with research and educational activities. The IDP research therefore aims for the transformation of academic and scientific know-how to practical applicability. In a first step this concerns directly the current Smart Rail 4.0 TMS-PAS project activities, that concentrate on timetabling issues. The IDP project team considers the integration of the line planning and the timetabling process as crucial for practical applications. To address this in the current research project, we present an application concept that enables the integration of these two major process steps in the transport service value-chain. Although it turns out from our research, that the technical requirements for the integration of the process can be satisfied, rules and conditions for a closer cooperation of the involved business units, the train operating companies and the infrastructure operating company, have to be improved and to be worked out in more detail. In addition to a detailed application concept with use cases for the timetabling process we propose a methodology for computer aided timetable generation based on the central planning object known as ‘service intention’. The service intention can be used to iteratively develop the timetable relying on a ‘progressive feasibility assessment’, a feature that is requested in practice. Our proposed model is based on the ‘track-choice’ and line rotation extension of the commonly known method for the generation of periodic event schedules ‘PESP’. The extension makes use of the track infrastructure representation which is also used in the line planning and timetabling system Viriato. This system that is widely used by public transport planners and operators. With the help of Viriato, it is rather easy to configure the timetabling problem in sufficient detail. On the other side, the level of detail of the considered data is light enough to algorithmically solve practical timetabling problems of realistic sizes. Taking into consideration the technical and operational constraints given by rolling stock, station and track topology data on one hand, and the commercial requirements defined by a given line concept on the other, the method presented generates periodic timetables including train-track assignments. In the first step, the standardized data structure ‘service intention’ represents the line concept consisting of train paths and frequencies. Due to the utilization of infrastructure-based track capacities, we are also able to assess the feasibility of the line concept given. Additionally, the method allows for handling temporary resource restrictions (e.g. caused by construction sites or operational disturbances). In order to assess the performance of the resulting timetable we present a framework for performance measurement that addresses the customer convenience (in terms of start-to-end travel time) as well as operational stability requirements (in terms of delay sensitivity and critical relations)

    Dispatching and Rescheduling Tasks and Their Interactions with Travel Demand and the Energy Domain: Models and Algorithms

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    Abstract 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

    Algorithm Engineering in Robust Optimization

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    Robust optimization is a young and emerging field of research having received a considerable increase of interest over the last decade. In this paper, we argue that the the algorithm engineering methodology fits very well to the field of robust optimization and yields a rewarding new perspective on both the current state of research and open research directions. To this end we go through the algorithm engineering cycle of design and analysis of concepts, development and implementation of algorithms, and theoretical and experimental evaluation. We show that many ideas of algorithm engineering have already been applied in publications on robust optimization. Most work on robust optimization is devoted to analysis of the concepts and the development of algorithms, some papers deal with the evaluation of a particular concept in case studies, and work on comparison of concepts just starts. What is still a drawback in many papers on robustness is the missing link to include the results of the experiments again in the design

    Vulnerability assessment modelling for railway networks

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    Railway networks are prone to many different potential disruptive events such as technical failures (e.g. the failure of aging components), natural disasters (e.g. flooding) and intentional man-made disasters (e.g. trespass and suicide). Assessing the vulnerability of railway networks can help infrastructure managers to create the right preventive strategies to improve the robustness and the resilience of railway networks before the occurrence of disruptions. This study proposes a stochastic-vulnerability analysis model that enables the critical components of railway networks to be identified. The model is developed using a discrete event simulation technique. Its framework includes modules for assigning the disruption to the network components, predicting the network vulnerability, in terms of passenger delays and journey cancellations, and calculating the risk-based criticality of network components. Finally, an example application of the model is presented using a part of the East Midland railway network in UK

    Adaptive railway traffic control using approximate dynamic programming

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    This study presents an adaptive railway traffic controller for real-time operations based on approximate dynamic programming (ADP). By assessing requirements and opportunities, the controller aims to limit consecutive delays resulting from trains that entered a control area behind schedule by sequencing them at critical locations in a timely manner, thus representing the practical requirements of railway operations. This approach depends on an approximation to the value function of dynamic programming after optimisation from a specified state, which is estimated dynamically from operational experience using reinforcement learning techniques. By using this approximation, the ADP avoids extensive explicit evaluation of performance and so reduces the computational burden substantially. In this investigation, we explore formulations of the approximation function and variants of the learning techniques used to estimate it. Evaluation of the ADP methods in a stochastic simulation environment shows considerable improvements in consecutive delays by comparison with the current industry practice of First-Come-First-Served sequencing. We also found that estimates of parameters of the approximate value function are similar across a range of test scenarios with different mean train entry delays

    Danish Key Performance Indicators for Railway Timetables

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    Based on the first common list of Danish railway timetable evaluation criteria this paper presents a series of existing and newly developed key performance indicators (KPI) for railway timetables. Measuring the level of timetable capacity consumption is done by the well-known UIC 406 methodology. By introducing the concept of timetable patterns it becomes possible to measure how systematic a given timetable is. Robustness of the timetable depends much on the complexity of the planned railway traffic. With the application of timetable fix points a new powerful tool becomes available to measure the robustness potential of a timetable. Societal acceptance of an implemented timetable is crucial for its success. It can be measured with satisfaction surveys. These must be conducted by an independent non-departmental organization to ensure objectivity, as it is done by “Passenger Focus” in the United Kingdom. Short travel and transfer times make the railway competitive. The degree of deviation from the shortest possible travel and transfer time gives an overview of the socio-economic attractiveness of a given timetable. The new KPI have proven useful in their first trial. Most of the presented KPI must be calculated manually but have a high potential to be automated and integrated into future timetabling software packages. Few of the KPI demand a high level of knowledge about railway infrastructure characteristics and basic timetable train path structures. This makes a future automation more difficult. The first trial of the recommended timetable KPI has shown further development possibilities by e.g. looking separately at railway stations when applying the UIC 406 methodology and considering timetable pattern differences when calculating how systematic a timetable is

    Evaluation of Actual Timetables and Utilization Levels of West Midlands Metro Using Event-Based Simulations

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    The performance of the West Midlands Metro in the United Kingdom is analyzed in the present study by evaluating the existing timetables of the metro system. Using SIMUL8 computer software, a discrete event-based simulation prototype modeling the metro system is developed and implemented. The model adequately describes the performance of the West Midlands Metro system. By running simulations, the overall utilization level of the metro system is calculated. The results of the simulation model indicate that the metro system is being underutilized. The low utilization rates indicate a potential for the introduction of new services capable of exploiting the existing infrastructure and improving the utilization levels of the existing metro system; For example, the potential of using the current metro system for urban freight transport could be a new service of interest and provide scope for further research
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