Train driver automation strategies to mitigate signals passed at danger on South African railways

A research project report submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, in fulfillment of the requirements for the degree of Masters in Engineering. Date 2018/04/18Train derailments or collisions have the potential to result in catastrophic loss of life and/or destruction of property. Ever higher demands for train density (i.e. trains per hour for a given section of track) as well as the catastrophic results when accidents do occur have given rise to the development of railway signalling systems as mitigation measures (Rolt, 2009; Theeg & Vlasenko (2009b). Signals Passed At Danger (SPADs) refers to when a train driver passes a stop signal without authority and is one of the typical causes of such accidents resulting in significant damages reported within Transnet Freight Rail (TFR) in recent years. Studies have shown human train driver error and violation of signals to be a significant cause of SPAD events. This study investigated the application of train driver automation as a mitigation measure against SPADs within the South African railway environment in general and TFR in particular. The study was qualitative in nature, following a model development methodology and used in-depth, semi-structured interviews with railway signalling engineers for data collection. The primary goal was defined to be the development of a train driver function automation method that could be considered the most appropriate within the TFR operational environment. The study determined the most appropriate method to be that of having a human driver with technical supervision. In this arrangement, the human driver could remain in his conventional role of driving the train but with a technical supervision system superimposed that automatically intervenes if a train driver exceeds his movement authority (e.g. Automatic Train Protection or ATP). This approach mitigates many of the costs imposed by human failure associated with SPAD events, yet retains the value of human flexibility which is especially useful under abnormal circumstances.MT 201

The role of data visualization in Railway Big Data Risk Analysis

Big Data Risk Analysis (BDRA) is one of the possible alleys for the further development of risk models in the railway transport. Big Data techniques allow a great quantity of information to be handled from different types of sources (e.g. unstructured text, signaling and train data). The benefits of this approach may lie in improving the understanding of the risk factors involved in railways, detecting possible new threats or assessing the risk levels for rolling stock, rail infrastructure or railway operations. For the efficient use of BDRA, the conversion of huge amounts of data into a simple and effective display is particularly challenging. Especially because it is presented to various specific target audiences. This work reports a literature review of risk communication and visualization in order to find out its applicability to BDRA, and beyond the visual techniques, what human factors have to be considered in the understanding and risk perception of the infor-mation when safety analysts and decision-makers start basing their decisions on BDRA analyses. It was found that BDRA requires different visualization strategies than those that have normally been carried out in risk analysis up to now

Impacts of Unattended Train Operations (UTO) on Productivity and Efficiency in Metropolitan Railways

Urban metro subway systems (metros) around the world are choosing increasing levels of automation for new and existing lines: the global length of metro lines capable of unattended train operation (UTO) is predicted to triple in the next 10 years. Despite significant investment in this technology, empirical evidence for the financial and service quality impacts of UTO in metros remains scarce. This study used questionnaires and semistructured interviews with the Community of Metros and Nova Group benchmarking groups to assemble emerging evidence of how automation affected costs, staffing, service capacity, and reliability. The results from an analysis of data from 23 lines suggested that UTO could reduce staff numbers by 30% to 70%, with the amount of wage cost reduction depending on whether staff on UTO lines were paid more. On the basis of the experience of seven metros, the capital costs of lines capable of UTO were higher, but the internal rate of return had been estimated by two metros at 10% to 15%. Automated lines were capable of operating at the highest service frequencies of up to 42 trains per hour, and the limited available data suggested that automated lines were more reliable. The findings indicated that UTO was a means to a more flexible and reliable operating model that could increase metro productivity and efficiency. The study identified important work needed to understand the impacts of UTO and identify where statistical analyses would add value once sufficiently large data sets became available

Railway freight transport and logistics: Methods for relief, algorithms for verification and proposals for the adjustment of tunnel inner surfaces

In Europe, the attention to efficiency and safety of international railway freight transport has grown in recent years and this has drawn attention to the importance of verifying the clearance between vehicle and lining, mostly when different and variable rolling stock types are expected. This work consists of defining an innovative methodology, with the objective of surveying the tunnel structures, verifying the clearance conditions, and designing a retrofitting work if necessary. The method provides for the use of laser scanner, thermocameras, and ground penetrating radar to survey the geometrical and structural conditions of the tunnel; an algorithm written by the authors permits to verify the clearances. Two different types of works are possible if the inner tunnel surfaces interfere with the profile of the rolling stock passing through: modification of the railroad track or modification of the tunnel intrados by mean milling of its lining. The presented case study demonstrates that the proposed methodology is useful for verifying compatibility between the design vehicle gauge and the existing tunnel intrados, and to investigate the chance to admit rolling stocks from different states. Consequently, the results give the railway management body a chance to perform appropriate measurements in those cases where the minimum clearance requirements are not achieved

Business optimization through automated signaling design

M.Ing. (Engineering Management)Abstract: Railway signaling has become pivotal in the development of railway systems over the years. There is a global demand for upgrading signaling systems for improved efficiency. Upgrading signaling systems requires new signaling designs and modifications to adjacent signaling systems. The purpose of this research is to compare manually produced designs with design automation by covering the framework of multiple aspects of railway signaling designs in view of business optimization using computer drawings, programming software language and management of signaling designs. The research focuses on design automation from the preliminary design stage to the detailed design stage with the intention of investigating and resolving a common project challenge of time management. Various autonomous methods are used to seek improvement on the detailed design phase of re-signaling projects. An analysis on the project’s duration, resources and review cycles is conducted to demonstrate the challenges that are faced during the design of a project. Signaling designs are sophisticated and crucial in an ever-changing railway environment. As a result, there is a demand for efficiency and knowledge within railway signaling to achieve successful completion project target dates. A quantitative approach is used to identify the gaps leading to delays and best practices are applied using a comparative analysis to remediate on any snags that may potentially extend the project duration. The results illustrate that the resources required when automating detailed designs are reduced by two thirds for cable plans and book of circuits and reduced by one third for source documents. Successively, the projects benefit with reduced organizational resources, reduced design durations and reduced design review cycles. This research concludes that software integration of the signaling designs due to the efficiency and innovation of the selected computer drawing software and programming software language such as AutoCAD required less resources for computer drawings that are generated using automation tools compared to computer drawings that are generated manually. The resources required when automating the generation of signaling detailed designs are reduced for cable plans, book of circuits and source documents. This means that the business is optimized by utilizing less resources and subsequently delays are reduced during the design stage

Learning from accidents : machine learning for safety at railway stations

In railway systems, station safety is a critical aspect of the overall structure, and yet, accidents at stations still occur. It is time to learn from these errors and improve conventional methods by utilizing the latest technology, such as machine learning (ML), to analyse accidents and enhance safety systems. ML has been employed in many fields, including engineering systems, and it interacts with us throughout our daily lives. Thus, we must consider the available technology in general and ML in particular in the context of safety in the railway industry. This paper explores the employment of the decision tree (DT) method in safety classification and the analysis of accidents at railway stations to predict the traits of passengers affected by accidents. The critical contribution of this study is the presentation of ML and an explanation of how this technique is applied for ensuring safety, utilizing automated processes, and gaining benefits from this powerful technology. To apply and explore this method, a case study has been selected that focuses on the fatalities caused by accidents at railway stations. An analysis of some of these fatal accidents as reported by the Rail Safety and Standards Board (RSSB) is performed and presented in this paper to provide a broader summary of the application of supervised ML for improving safety at railway stations. Finally, this research shows the vast potential of the innovative application of ML in safety analysis for the railway industry

Transport 2040 : analysis of technical developments in transport - maritime, air, rail and road

A number of technical and socio-technical factors are driving the development and adoption of automation. The report, Transport 2040: Automation, Technology, Employment – The Future of Work, provided an overview of the most important trends forecasted to affect the global transport sector by 2040. This current report provides additional details of that assessment. The research conducted is guided by a transport-technology analytical model that provides a structure for a systematic review across different modes of transport. This report reviews, in particular, the transportation technology through the lens of transport vehicles (e.g. ships, trucks, trains, aircraft) and the technical infrastructure that is needed for the operation of the vehicle (e.g. waterways and harbours, roads, railway tracks and freight terminals, as well as controlled airspace and airports).https://commons.wmu.se/lib_reports/1076/thumbnail.jp