DFT modeling approach for operational risk assessment of railway infrastructure

Reliability engineering of railway infrastructure aims to understand failure processes and to improve the efficiency and effectiveness of investments and maintenance planning such that a high quality of service is achieved. While formal methods are widely used to verify the design specifications of safety-critical components in train control, quantitative methods to analyze the service reliability associated with specific system designs are only starting to emerge. In this paper, we strive to advance the use of formal fault-tree modeling for providing a quantitative assessment of the railway infrastructure's service reliability in the design phase. While, individually, most subsystems required for route-setting and train control are well understood, the system's reliability to globally provide its designated service capacity is less studied. To this end, we present a framework based on dynamic fault trees that allows to analyze train routability based on train paths projected in the interlocking system. We particularly focus on the dependency of train paths on track-based assets such as switches and crossings, which are particularly prone to failures due to their being subject to weather and heavy wear. By using probabilistic model checking to analyze and verify the reliability of feasible route sets for scheduled train lines, performance metrics for reliability analysis of the system as a whole as well as criticality analysis of individual (sub-)components become available. The approach, which has been previously discussed in our paper at FMICS 2019, is further refined, and additional algorithmic approaches, analysis settings and application scenarios in infrastructure and maintenance planning are discussed

Analysis of a Train-operating Company’s Customer Service System during Disruptions:Conceptual Requirements for Gamifying Frontline Staff Development

This paper provides an account of an action research study into the systemic success factors which help frontline staff react to and recover from a rail service disruption. This study focuses on the effective use of information during a disruption to improve customer service, as this is a priority area for train-operating companies (TOCs) in Great Britain. A novel type of systems thinking, known as Process-Oriented Holonic Modelling (PrOH), has been used to investigate and model the ‘Passenger Information During Disruption’ (PIDD) system. This paper presents conceptual requirements for a gamified learning environment; it describes ‘what’; ‘how’ and ‘when’ these systemic success factors could be gamified using a popular disruption management reference framework known as the Mitigate, Prepare, React and Recover (MPRR) framework. This paper will interest managers of and researchers into customer service system disruptions, as well as those wishing to develop new gamified learning environments to improve customer service systems

Train planning in a fragmented railway: a British perspective

Train Planning (also known as railway scheduling) is an area of substantial importance to the success of any railway. Through train planning, railway managers aim to meet the needs of customers whilst using as low a level of resources (infrastructure, rolling stock and staff) as possible. Efficient and effective train planning is essential to get the best possible performance out of a railway network. The author of this thesis aims, firstly, to analyse the processes which are used to develop train plans and the extent to which they meet the objectives that they might be expected to meet and, secondly, to investigate selected new and innovative software approaches that might make a material difference to the effectiveness and/or efficiency of train planning processes. These aims are delivered using a range of primarily qualitative research methods, including literature reviews, interviews, participant observation and case studies, to understand these processes and software. Conclusions regarding train planning processes include how the complexity of these processes hinders their effectiveness, the negative impact of the privatisation of British Rail on these processes and the conflicting nature of objectives for train planning in the privatised railway. Train planning software is found not to adequately support train planners in meeting the objectives they are set. The potential for timetable generation using heuristics and for timetable performance simulation to improve the effectiveness of train planning are discussed and recommendations made for further research and development to address the limitations of the software currently available

Effective, Comfortable, and Sustainable Railway Systems: Decision Models for Optimal Asset Management and Scenarios Analysis

Millions of passengers worldwide rely on a fast, competitive, and reliable transit system for daily transportation. The American infrastructure report card 2017 assigned a level “D-” to the USA’s transit sector that means “poor” condition. The Canadian report card in 2016 assigned a grade of “Fair” to fixed assets (e.g. stations and tunnels) of the transport system; this indicates that such assets “require attention”. Meanwhile, 25% of such fixed assets were ranked in poor and very poor condition. In periods of 2016 – 2018, the Société de Transport de Montréal (STM) has invested the amount of C$2.2 billion, or 78% of its total capital expenditure for metro system maintenance and upgrading. Extensive deterioration of already aged metro systems in North America complicates managing the network while coping with the increased demand and the corresponding need to plan for capital upgrades with a restricted annual budget. Effective planning to rehabilitate existing assets and expand new ones while respecting constraints is key to the success of transit-oriented strategies. However, without a comprehensive multi-criteria decision-making procedure, it is impossible to achieve the optimal actions at the right time within the given budget. The main objective of this research is to develop a comprehensive model for managing urban railways, such as the metro, that supports strategic decisions to maintain the highest level of convenience, safety, comfort and reliability in the metropolitan area. To overcome the gaps found in the literature, these proposed steps should be used: Step I: Developing an understanding of convenience with special concentration on the level of service from the passenger’s perspective. The idea is to model, quantitatively and practically, aspects relevant to the user convenience for transit vehicle’s comfort. Step II: Development of a decision-making model to mimic the operation of the transit systems capturing indirect impacts such as human development and sustainability. Step III: Development of an optimization model to analyze investment scenarios for the upgrade and expansion of the railway network, while up-keeping the existing operation at acceptable levels of service, guiding policies, and respecting budget limitation. This includes the relationships between the transit system and human development issues, addressing fighting poverty; supporting accessibility to health, education and job centers; and encouraging the modal shift away from the automobiles. The proposed models could also be used by public transit systems such as Tramway, Bus Rapid Transit (BRT), Light Rail Transit (LRT), traditional buses and metro to guide planning for their maintenance, upgrade and expansion to achieve higher levels of convenience and reliability encouraging transit ridership

Electric and hydrogen rail : Potential contribution to net zero in the UK

Acknowledgements  This research was carried out under the UK Energy Research Centre (UKERC) as part of the ADdressing Valuation of Energy and Nature Together (ADVENT) funded project. Funding was received from the Natural Environment Research Council (NE/M019691/1), United Kingdom and the School of Biological Sciences, University of Aberdeen, United Kingdom. The authors would also like to thank Dr Christian Brand, University of Oxford, for giving them access to the Transport Energy and Air Pollution Model (TEAM-UK).Peer reviewedPublisher PD

State-of-the-art in managing reliability in mega railway projects.:A systematic literature review

Mega Railway Projects (MRPs) are expensive and account for an increasing per-centage of many a nation’s annual infrastructure expenditure. These MRPs fre-quently exceed their budget and schedule. The challenge of achieving reliability or availability targets stands out as a contributing factor to these overruns. A robust and targeted Reliability, Availability, and Maintainability (RAM) process, which covers systems and subsystems that comprise the railway, that is imbedded in the project from the outset and that is managed throughout the life cycle of the project, is crucial for success. However, a RAM process for MRPs is not readily available. While BS EN 50126-11sets out the required RAM related tasks there is no guidance on how these tasks are to be undertaken or managed. This omission is likely to increase the challenge faced by RAM or Systems engineers as they put forth their case for ring-fenced funds and labour at the outset of an MRP. It is therefore important that RAM on an MRP is reviewed so that next steps in devel-oping robust RAM process plan guidelines can be determined. The authors of this paper discuss why RAM is undertaken and the conceptualisation of RAM along with its fundamental features. Its application on railways focusing on RAM techni-ques and BS EN 50126-1 is outlined. A Systematic Literature Review (SLR) is under-taken to show the state-of-the-art by using a meta and content analysis within the context of railway systems, RAM techniques, RAM standards and Reliability levels. Furthermore, a set of Derived RAM requirements (DRR) based on BS EN 50126-1 are derived to determine the critical areas of RAM and are thus recommended for further development by researchers or RAM practitioner

Modelling and simulation of rail passengers to evaluate methods to reduce dwell times

The paper outlines a feasibility study using modelling and simulation to reduce dwell times and increase rail network capacity. We use agent based modelling, where passengers are treated as a separate entities, basing their movements on rules from the Social Force Model (SFM), proposed by Helbing to model pedestrian dynamics. Implementing this SFM, together with a novel decision making system for passengers' door choices, a mesoscopic model is produced of the platform, train and passengers. An outline of the modelling process is presented, along with a critical analysis of the final model. Analyses are conducted to evaluate novel concepts in train and platform design, to reduce loading times, using passengers with a range of attributes. In a simulation experiment, four concepts (wider doors, designated boarding/alighting doors, and an active passenger information system) are assessed, with the latter two giving reductions in loading times of 7.0% and 7.3%