Overview of Infrastructure Charging, part 4, IMPROVERAIL Project Deliverable 9, “Improved Data Background to Support Current and Future Infrastructure Charging Systems”

Improverail aims are to further support the establishment of railway infrastructure management in accordance with Directive 91/440, as well as the new railway infrastructure directives, by developing the necessary tools for modelling the management of railway infrastructure; by evaluating improved methods for capacity and resources management, which allow the improvement of the Life Cycle Costs (LCC) calculating methods, including elements related to vehicle - infrastructure interaction and external costs; and by improving data background in support of charging for use of railway infrastructure. To achieve these objectives, Improverail is organised along 8 workpackages, with specific objectives, responding to the requirements of the task 2.2.1/10 of the 2nd call made in the 5th RTD Framework Programme in December 1999.This part is the task 7.1 (Review of infrastructure charging systems) to the workpackage 7 (Analysis of the relation between infrastructure cost variation and diversity of infrastructure charging systems).Before explaining the economic characteristics of railway and his basic pricing principles, authors must specify the objectives of railways infrastructure charging.principle of pricing ; rail infrastructure charging ; public service obligation ; rail charging practice ; Europe ; Improverail

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

DC railway power supply system reliability evaluation and optimal operation plan

With the continuous and rapid development of the economy and the acceleration of urbanisation, public transport in cities has entered a period of rapid development. Urban rail transit is characterised by high speed, large traffic volume, safety, reliability and punctuality, which are incomparable with those of other forms of public transport. The traction power supply system (TPSS) is an important part of an electrified railway, and its safety issues are increasingly prominent. Different from the substation in a general power system, the load of a TPSS has a great impact on the traction transformer; moreover, in order to ensure normal operation of the train in case of failure, the traction substation must be able to access a cross-district power supply, as it has a high demand for reliable operation. The safe and reliable operation of DC TPSSs is the basis of the whole urban railway transit system. Previous studies have investigated the reliability of the TPSS main electrical wiring system. However, the impact of traction load and the actual operation of trains on system reliability has not been considered when designing a DC railway power supply system. The purpose of the research for this thesis is to find an optimal system operation plan for urban railways, considering load characteristics. This thesis begins with a review of the main arrangements of DC railway power supply systems and the literature on railway reliability studies. A model of single train simulation and a power supply system is established in MATLAB. The developed simulator is then integrated with a TPSS reliability model to evaluate the energy and reliability performance of DC railway power systems. Based on the train traction load model and train schedule, a comprehensive method for evaluating a DC TPSS considering traction load is proposed. Through simulation of the actual operation of the train group, the system energy consumption and substation life loss generated under different train operation diagrams and schedules are compared to provide a reference for the reasonable design of the timetable. Taking the life loss and energy consumption of the whole TPSS as the objective function, a genetic algorithm is used to optimise the train speed, coasting velocity, station dwell time and headway to find the optimal operation strategy. This is illustrated with a case study of the Singapore East–West metro line. The study has addressed the following issues: development of a multi-train power simulator, evaluation of reliability performance, and finally the search for an optimal operation plan. The train running diagram and timetable are optimised jointly. This can help railway operators make decisions for an optimal operation plan and reduce the operation risk of the power system

A multidimensional examination of performances of HSR (High-Speed Rail) systems

This paper deals with a multidimensional examination of the infrastructural, technical/technological, operational, economic, social, and environmental performances of high-speed rail (HSR) systems, including their overview, analysis of some real-life cases, and limited (analytical) modeling. The infrastructural performances reflect design and geometrical characteristics of the HSR lines and stations. The technical/technological performances relate to the characteristics of rolling stock, i.e., high-speed trains, and supportive facilities and equipment, i.e., the power supply, signaling, and traffic control and management system(s). The operational performances include the capacity and productivity of HSR lines and rolling stock, and quality of services. The economic performances refer to the HSR systems’ costs, revenues, and their relationship. The social performances relate to the impacts of HSR systems on the society such as congestion, noise, and safety, and their externalities, and the effects in terms of contribution to the local and global/country socialeconomic development. Finally, the environmental performances of the HSR systems reflect their energy consumption and related emissions of green house gases, land use, and corresponding externalities.</p

A review on artificial intelligence in high-speed rail

High-speed rail (HSR) has brought a number of social and economic benefits, such as shorter trip times for journeys of between one and five hours; safety, security, comfort and on-time commuting for passengers; energy saving and environmental protection; job creation; and encouraging sustainable use of renewable energy and land. The recent development in HSR has seen the pervasive applications of artificial intelligence (AI). This paper first briefly reviews the related disciplines in HSR where AI may play an important role, such as civil engineering, mechanical engineering, electrical engineering and signalling and control. Then, an overview of current AI techniques is presented in the context of smart planning, intelligent control and intelligent maintenance of HSR systems. Finally, a framework of future HSR systems where AI is expected to play a key role is provided

Maximum risk reduction with a fixed budget in the railway industry

Decision-makers in safety-critical industries such as the railways are frequently faced with the complexity of selecting technological, procedural and operational solutions to minimise staff, passengers and third parties’ safety risks. In reality, the options for maximising risk reduction are limited by time and budget constraints as well as performance objectives. Maximising risk reduction is particularly necessary in the times of economic recession where critical services such as those on the UK rail network are not immune to budget cuts. This dilemma is further complicated by statutory frameworks stipulating ‘suitable and sufficient’ risk assessments and constraints such as ‘as low as reasonably practicable’. These significantly influence risk reduction option selection and influence their effective implementation. This thesis provides extensive research in this area and highlights the limitations of widely applied practices. These practices have limited significance on fundamental engineering principles and become impracticable when a constraint such as a fixed budget is applied – this is the current reality of UK rail network operations and risk management. This thesis identifies three main areas of weaknesses to achieving the desired objectives with current risk reduction methods as: Inaccurate, and unclear problem definition; Option evaluation and selection removed from implementation subsequently resulting in misrepresentation of risks and costs; Use of concepts and methods that are not based on fundamental engineering principles, not verifiable and with resultant sub-optimal solutions. Although not solely intended for a single industrial sector, this thesis focuses on guiding the railway risk decision-maker by providing clear categorisation of measures used on railways for risk reduction. This thesis establishes a novel understanding of risk reduction measures’ application limitations and respective strengths. This is achieved by applying ‘key generic engineering principles’ to measures employed for risk reduction. A comprehensive study of their preventive and protective capability in different configurations is presented. Subsequently, the fundamental understanding of risk reduction measures and their railway applications, the ‘cost-of-failure’ (CoF), ‘risk reduction readiness’ (RRR), ‘design-operationalprocedural-technical’ (DOPT) concepts are developed for rational and cost-effective risk reduction. These concepts are shown to be particularly relevant to cases where blind applications of economic and mathematical theories are misleading and detrimental to engineering risk management. The case for successfully implementing this framework for maximum risk reduction within a fixed budget is further strengthened by applying, for the first time in railway risk reduction applications, the dynamic programming technique based on practical railway examples

Using information engineering to understand the impact of train positioning uncertainties on railway subsystems

Many studies propose new advanced railway subsystems, such as Driver Advisory System (DAS), Automatic Door Operation (ADO) and Traffic Management System (TMS), designed to improve the overall performance of current railway systems. Real time train positioning information is one of the key pieces of input data for most of these new subsystems. Many studies presenting and examining the effectiveness of such subsystems assume the availability of very accurate train positioning data in real time. However, providing and using high accuracy positioning data may not always be the most cost-effective solution, nor is it always available. The accuracy of train position information is varied, based on the technological complexity of the positioning systems and the methods that are used. In reality, different subsystems, henceforth referred to as ‘applications’, need different minimum resolutions of train positioning data to work effectively, and uncertainty or inaccuracy in this data may reduce the effectiveness of the new applications. However, the trade-off between the accuracy of the positioning data and the required effectiveness of the proposed applications is so far not clear. A framework for assessing the impact of uncertainties in train positions against application performance has been developed. The required performance of the application is assessed based on the characteristics of the railway system, consisting of the infrastructure, rolling stock and operational data. The uncertainty in the train positioning data is considered based on the characteristics of the positioning system. The framework is applied to determine the impact of the positioning uncertainty on the application’s outcome. So, in that way, the desired position resolution associated with acceptable application performance can be characterised. In this thesis, the framework described above is implemented for DAS and TMS applications to understand the influence of positioning uncertainty on their fundamental functions compared to base case with high accuracy (actual position). A DAS system is modelled and implemented with uncertainty characteristic of a Global Navigation Satellite System (GNSS). The train energy consumption and journey time are used as performance measures to evaluate the impact of these uncertainties compared to a base case. A TMS is modelled and implemented with the uncertainties of an on-board low-cost low-accuracy positioning system. The impact of positioning uncertainty on the modelled TMS is evaluated in terms of arrival punctuality for different levels of capacity consumption. The implementation of the framework for DAS and TMS applications determines the following: • which of the application functions are influenced by positioning uncertainty; • how positioning uncertainty influences the application output variables; • how the impact of positioning uncertainties can be identified, through the application output variables, whilst considering the impact of other railway uncertainties; • what is the impact of the underperforming application, due to positioning uncertainty, on the whole railway system in terms of energy, punctuality and capacity

How to make modal shift from road to rail possible in the European transport market, as aspired to in the EU Transport White Paper 2011

The total demand for freight transport in Europe has increased significantly in recent decades, but most of it has been handled by road transport. To fulfil the modal shift targets set in the EU White Paper 2011, it will be necessary to double rail’s market share from today’s 18 %, by 2050. Translating this into reality means rail will have to handle 3 to 4 times the cargo volume it does today. With this in mind, the paper develops a vision of an efficient rail freight system in 2050. Methodology To achieve the above objective, the research applies literature survey and group discussion methodology and applying a system approach. Keeping on board the EU Transport White Paper 2011 modal shift targets, as well as future freight demand and customer requirements, the current research attempts to answer the following three critical questions: -How can rail offer the quality of service that will attract customers and fulfil the targets? - How can rail offer its customers a price that is competitive with road? - How can rail offer the capacity to meet the increased demand from modal shift

Development of an upgrade selection process for railway renewal projects

Currently, many railway systems need to be upgraded to meet the demand for rapidly increasing railway capability, environmental concerns and customer satisfaction, while there is a lack of the right models and tools required to support the early decision making stage of railway renewal projects. In this thesis, a new railway selection upgrade process is proposed, which aims to support early stage decision-making in railway renewal projects by finding the most appropriate solutions to take forward for more detailed consideration. The railway selection upgrade process consists of modelling, simulation, split into macros-assessment and micro-simulation, and evaluation. A high-level feasibility analysis model is developed for the macro-assessment, to help engineers efficiently select the most promising upgrade options for further detailed consideration using microscopic simulation. This process provides a quick and efficient way to quantify evaluation functions, based on the 4Cs (capacity, carbon, customer satisfaction and cost) framework, to give a final suggestion on the most appropriate upgrade options. Two case studies, based on the East Coast Main Lines and the Northern Ireland railway network, are presented in order to demonstrate the application and verify the feasibility of the high-level feasibility analysis model and the railway upgrade selection process