Proceedings of the Institution of Mechanical Engineers,Part F: Journal of Rail and Rapid Transit

Despite the increasing trend for high-fidelity train simulator procurement in the rail industry, current research suggests that simulators are extremely underutilised, which points to ineffective integration arising from one or more disconnects in the management layers. This paper presents a study that set out to: profile the design of driver learning frameworks; investigate how simulators were being integrated; and determine key criteria for simulator acceptance. Data were collected from 61 industry end-users, mostly train drivers, in six rail organisations, and analysed thematically. The findings revealed three Rs that reflected perceptions of poor integration and comprised the dominant end-user evaluation criteria for simulator utility; these were: (i) Reality; (ii) Relevancy; and (iii) Reliability. This paper explores the problem of ineffective integration by using and applying a Robocop allegory, in order to disentangle the dynamic shared between the systemic and cultural influences of the organisation, when new technology is introduced in a highly regulated environment. The paper concludes by presenting three prime directives, triangulated from the study and current literature, to transcend the issues impeding the path of effective simulator integration in rail, and overcome the ‘Robocop problem’ as it applies to this industry.

Fidelity evaluations are an important part of simulation design. They identify any gaps in fidelity, help establish the simulator’s overall validity, and their outcomes may significantly enhance the correspondence between the simulated environment and the real world. However, fidelity evaluations are easily overwhelmed by the technical focus in the simulator commissioning and acceptance processes, and too often, are overlooked or undermined in favour of remaining within the scope of the original specification. This article presents a fidelity evaluation that was applied to a railway safety research simulator after it was deployed for operational use. The evaluation was stratified according to the physical, functional and task-based strands of fidelity, and undertaken in a collaborative research approach that integrated the relative domain, task, simulation and human factors-based expertise of a team of evaluators. Furthermore, the evaluation also examined the simulator’s tractability in terms of its intended users (researchers), and investigated the scope for scenario development. The findings revealed several opportunities for improving the fidelity of the simulator for research (and training) applications, but also identified a number of critical deficiencies in its underlying architecture. This paper discusses the outcomes of the evaluation in terms of the fidelity expectations of the developer and user, and the tension encountered when trying to adjust these post-deployment. Lastly, it provides some clarification between what to improve and what can be improved, when the proverbial train has, for all intents and purposes, left the station.

The use of state-of-the-art technology to collect and analyse data has significantly improved the effectiveness of safety studies. Currently, despite the fact that there are many safety systems deployed at railway crossings, only limited research has been conducted to evaluate which of these systems is the most effective in terms of costs and safety. This paper demonstrates a way to evaluate safety at railway crossings using a twin-pronged approach: a driving simulator and traffic simulation software. A number of outputs have been observed from a driving simulator, such as driver compliance rate, vehicle speed profile, acceleration profile, initial braking position and final braking position. The compliance percentage at passive crossings (67 and 72% for a stop sign and rumble strips, respectively) has lower compliance rates compared with active crossings (97 and 93% for flashing red light and in-vehicle audible warning, respectively) at an 80 km/h approach speed. Using a statistical analysis it is shown that speed and acceleration profiles can be used to differentiate the effectiveness of active and passive crossings. These indicators are interpreted and used as input to a traffic simulation, which assists in determining which safety device is more efficient. By integrating driving simulator and traffic simulation models, this approach can be applied to evaluate and compare safety performance without the need to install costly test beds at real railway crossings.

A computer simulation technique has been used to study and evaluate the potential for the application of hybrid locomotives to heavy haul operations on two typical track routes in Australia. The study envisages typical pit-to-port operations with large altitude changes. The train energy usage and the energy created by dynamic braking are analysed based on the simulation results. It is shown that the locomotives operate at an average power that is much less than full power. It is found that there is potential for hybrid heavy haul locomotive applications. Suggested methods and concept designs are proposed. Sizing of the energy storage system when it contained batteries, super-capacitors and flywheels was carried out for comparison purposes. The merits and problems with each concept are discussed.

The acceptable dynamic behaviour of railway locomotives is governed by different standards in different parts of the world. Some standards allow the use of multibody simulation tools (such as VAMPIRE, NUCARS, GENSYS and SIMPACK) in place of physical testing, but generally not for all locomotive tests within each standard. Virtual multibody locomotive models can allow simple analyses, such as for slightly modified and relocated locomotives, to be completed in less time, and lower cost and effort in comparison with physical type testing. Unfortunately, the detailed locomotive model acceptance procedures required to achieve this for locomotive designs do not presently exist. This paper discusses the methodology behind a proposed locomotive model acceptance procedure that is currently intended for Australian freight locomotives, although it can be modified to suit other countries and locomotive types. A review of relevant international standards was first undertaken to determine which tests to include and to draw from international best practice. A few case studies are then given to show how the proposed methodology can be implemented on a heavy haul locomotive model.

In order to validate prediction models of wheel squeal, a rolling contact test rig is used to investigate fundamental squeal behaviour. The vibration characteristics of the wheel are investigated using analytical and finite element methods, and by experimental impact hammer analysis, respectively. Accordingly, the lateral resonant frequencies and mode shapes of the wheel are determined. A dominant mode is identified based on this as the primary peak in the sound spectrum of squeal and is used as an indicator of the occurrence and magnitude of squeal. The lateral creep curves and amplitudes of wheel vibration at various rolling speeds are measured using a strain gauge technique and predicted. A simplified model including the interaction between lateral force and transverse vibration of the dominant mode is developed, and the experimental and simulated results show the sound pressure level and vibration velocity of the wheel increases substantially as the angle of attack reaches and exceeds the value around 8 mrad. The phenomenon of double peaks in the sound spectrum of wheel squeal is also investigated. It is found that the cause of double peaks is due to the wheel rotation and the frequency divergence of double peaks increases with rolling speed as predicted theoretically.

Rail squats or studs, being a sub-surface crack in a track below a depression of the rail surface, have been studied in the Australian CRC for Rail Innovation project R3.105, from a number of perspectives. Examination of squats on track by the Rail Corporation of NSW has revealed statistics about their distribution. Examination with optical and scanning electron microscopy at the University of Queensland has shown the frequent presence of a brittle white etching layer (WEL) on the rail surface. This has led to successful adaptation of eddy currents to detect WEL rather than cracks. Tests at the University of Queensland have investigated whether the WEL can form below the normal 720℃ needed to form austenite. Examination of crack surfaces shows beach marks indicative of growth in modes II and III. Neutron diffraction testing of Australian rail has shown residual stresses in a railhead with a WEL, similar to those reported elsewhere, but with a broad surface layer in compression, not a narrow running band. Elasto-plastic finite element simulation has shown residual compression transforms into residual shear at a crack tip, which increases that due to plastic deformation from successive wheel passages, tending to encourage the crack to continue in a direction of sub-surface growth. The rate of growth of squats measured on-track in Sydney shows crack growth that corresponds to a power law with a low exponent, implying that the stress intensity at the crack tip is not a strong function of crack length. This is partly due to the localised nature of contact stresses, which allows the crack to grow beyond the region loaded. However, accounting for this effect leads to the prediction of a smaller reduction in growth rate than that observed. It is likely the low exponent reflects a smaller effect of water on crack growth, as the crack enlarges. There is also a redistribution of contact loading that occurs as a crack grows.

Track buckling is a serious problem for railways. High longitudinal rail stresses contribute to problems such as track buckling, rail joint failure, rail breakage and failure of turnouts. The direct and indirect costs of track buckling problems are very high. The influences of rail temperature, stress-free temperature (SFT) and lateral misalignment of track on track buckling need comprehensive investigation. In this paper, an experimental design comprising strain gauges, thermocouples and rail stress sensors has been implemented on the Queensland Rail heavy haul 60 kg/m rail network. A new creep measurement technique using internal rail stress has been developed. The changes in rail neutral temperature due to the variation of actual rail temperature and the occurrence of rail creep in straight and curved track is quantified. Modes of differences of SFT in the two rails at a location, and of SFT in straight track and in curved track are discussed. The relationship of SFT to rail temperature is also presented. Daily variation in rail temperature due to ambient air temperature is presented. Field trials showed that SFT can vary by 2–3 ℃ during the day. Based on this finding and the derivation of an equation for change of SFT, an improvement in utilising rail creep measurements for assessing track condition has resulted. This finding suggests that it is possible to determine the SFT throughout a day rather than just a single SFT value. This paper also presents a simple track stability management tool that is based on two major parameters, namely rail stress and track resistance. Each parameter in the tool has been given three levels of value to determine the required preventive measures. Overall, the tool decides the need for speed restriction during hot weather based on the quantified parameters from the field trials and rail standards.

Track maintenance work is one of the most hazardous jobs in the rail industry. Track workers are in danger of being fatally injured by rail traffic either on the track they are working on or on adjacent tracks. The rail industry has developed many safe working procedures and protection systems to minimise the risk. The Australian rail industry is now trialling new technology that automatically warns the track workers of approaching trains. These technologies may be added to or ultimately replace the current safe working procedures. As there are different products and technologies available for track worker protection it is not clear which technology is best for the Australian rail environment. The CRC for Rail Innovation project ‘R3.120-Track Worker Protection Technology’ aims to identify and compare systems that improve protection for track workers. Commercially available systems use different types of technologies and have different safety integrity levels. The effectiveness of a safety system is not only dependent on the technology but also the track workers who operate and are protected by the system. Short-term trials may not highlight all issues across the systems’ life cycle so to analyse these socio-technical systems in a relatively short time period a specifically adapted hazard and operability (HAZOP) study is being undertaken. The HAZOP study evaluates both the technical and human factor aspects of the system utilising an expert team. Initially one of the commercially available track worker protection systems was selected as the base for the HAZOP and other track worker protection systems will be analysed based on the issues identified with the initial system. This paper discusses the ‘Track Worker Protection Technology’ project, the track worker protection technology that is available and the adapted HAZOP used to analyse a track worker safety system as a socio-technical system.

Inadequate consideration of human factors has been found to be a leading cause of unwanted consequences associated with control room systems. To guard against these events, many safety regulators have mandated that human factors are to be addressed as part of safety management, with Australian railways receiving the national mandate in January 2013. At the moment, as is the case in many parts of the world, Australian railways do not have their own dedicated standard or guide on how to integrate human factors. Fortunately, understanding of human factors in work systems has advanced significantly since the 1980s and a growing professional body of specialists is emerging. Alongside systems engineers and project managers, many human factors specialists are involved in the design of new systems. By attending to the contextual details, designs become more compatible with their human counterparts and numerous analytical tools and techniques have been developed for this purpose. Therefore, it would be advantageous for railway operators and systems engineers to know the types of activities human factors specialists are involved in and how they might contribute to human factors integration. A literature review was conducted to identify the integration approaches used by technology designers and various safety-critical domains. Additionally, a study was conducted to identify the human factors analytical tools and techniques that are typically used in control room settings. Findings from the study provide a useful snapshot of the types of activities human factors professionals are involved in, the tools and techniques they use and the areas currently being addressed that benefit from closer human factors attention.

Collisions between pedestrians and vehicles continue to be a major problem throughout the world. Pedestrians trying to cross roads and railway tracks without any caution are often highly susceptible to collisions with vehicles and trains. Continuous financial, human and other losses have prompted transport related organizations to come up with various solutions addressing this issue. However, the quest for new and significant improvements in this area is still ongoing. This work addresses this issue by building a general framework using computer vision techniques to automatically monitor pedestrian movements in such high-risk areas to enable better analysis of activity, and the creation of future alerting strategies. As a result of rapid development in the electronics and semi-conductor industry there is extensive deployment of CCTV cameras in public places to capture video footage. This footage can then be used to analyse crowd activities in those particular places. This work seeks to identify the abnormal behaviour of individuals in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM), Full-2D HMM and Spatial HMM to model the normal activities of people. The outliers of the model (i.e. those observations with insufficient likelihood) are identified as abnormal activities. Location features, flow features and optical flow textures are used as the features for the model. The proposed approaches are evaluated using the publicly available UCSD datasets, and we demonstrate improved performance using a Semi-2D Hidden Markov Model compared to other state of the art methods. Further we illustrate how our proposed methods can be applied to detect anomalous events at rail level crossings.

This paper describes the work being conducted in the Baseline Rail Level Crossing Video project, supported by the Australian rail industry and the Cooperative Research Centre for Rail Innovation. The paper discusses the limitations of near-miss data for analysis obtained using current level crossing occurrence reporting practices. The project is addressing these limitations through the development of a data collection and analysis system with an underlying level crossing accident causation model. An overview of the methodology and improved data recording process are described. The paper concludes with a brief discussion of benefits this project is expected to provide the Australian rail industry.

This paper describes a risk model for estimating the likelihood of collisions at low-exposure railway level crossings, demonstrating the effect that differences in safety integrity can have on the likelihood of a collision. The model facilitates the comparison of safety benefits between level crossings with passive controls (stop or give-way signs) and level crossings that have been hypothetically upgraded with conventional or low-cost warning devices. The scenario presented illustrates how treatment of a cross-section of level crossings with low-cost devices can provide a greater safety benefit compared with treatment with conventional warning devices for the same budget.

Railway bridges are long-life assets that deteriorate with age, use and poor maintenance practices. The rail industry is suffering from ever-increasing maintenance costs which are exacerbated by increased rail traffic and reduced maintenance opportunities. In addition, bridge managers are expected to maintain their assets at specified performance levels while enduring budget cuts and resource constraints. There is an increasing demand for bulk material transport leading to increased axle loads pushing bridge structures to their design loading limit. Making informed decisions for cost-effective condition assessment, maintenance, repairs, upgrades and replacements, often with inadequate and sometimes inaccurate data is a major challenge in the management of railway bridges. Due to these challenges, infrastructure planners require additional time to plan and prepare maintenance budgets, analyse, interpret and make decisions for bridge asset life management. Many of the bridge management systems utilised in Australia are generic and analyse faults at the network level. In many cases, a detailed analysis of individual elements will provide a better understanding of root causes of faults and allow for more informed decision-making on bridge life enhancement. A practical framework for life cycle management of Australian concrete and steel railway bridges was developed in this research. This framework is based on life cycle cost analysis and consists of bridge assessment, maintenance optimisation and implementation. The outcome of this research is a faster, more accurate system that improves the informed decision-making capability for life cycle cost management of railway bridges.

In Australia, and elsewhere, the movement of trains on long-haul rail networks is usually planned in advance. Typically, a train plan is developed to confirm that the required train movements and track maintenance activities can occur. The plan specifies when track segments will be occupied by particular trains and maintenance activities. On the day of operation, a train controller monitors and controls the movement of trains and maintenance crews, and updates the train plan in response to unplanned disruptions.

It can be difficult to predict how good a plan will be in practice. The main performance indicator for a train service should be reliability – the proportion of trains running the service that complete at or before the scheduled time.

We define the robustness of a planned train service to be the expected reliability. The robustness of individual train services and for a train plan as a whole can be estimated by simulating the train plan many times with random, but realistic, perturbations to train departure times and segment durations, and then analysing the distributions of arrival times. This process can also be used to set arrival times that will achieve a desired level of robustness for each train service.