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

Privatisation and Franchising of British Train Operations: the decline and derailment of the Great North Eastern Railway

As a result of the 1993 Railways Act, the British railways industry was privatised which resulted in the separation of ownership and control of the railway infrastructure (track, signals and stations) from that of passenger train operations. The Great North Eastern Railway (GNER), a major train operator, was unable to meet its contractual obligations shortly after successfully re-tendering for its second franchise. Within the context of incomplete contract theory, this paper discusses the main problems inherent in the franchising process and which specifically contributed to the collapse of GNER. In particular, the paper argues that the fragmented structure of asset ownership, the lack of coordination and investment incentives and flaws in the franchise method itself explain the demise of GNER and have undermined the general objectives of railway privatisation

Prediction of metal pm emission in rail tracks for condition monitoring application

Exposure to particulate material (PM) is a major health concern in megacities across the world which use trains as a primary public transport. PM emissions caused by railway traffic have hardly been investigated in the past, due to their obviously minor influence on the atmospheric air quality compared to automotive transport. However, the electrical train releases particles mainly originate from wear of rails track, brakes, wheels and carbon contact stripe which are the main causes of cardio-pulmonary and lung cancer. In previous reports most of the researchers have focused on case studies based PM emission investigation. However, the PM emission measured in this way doesn’t show separately the metal PM emission to the environment. In this study a generic PM emission model is developed using rail wheel-track wear model to quantify and characterise the metal emissions. The modelling has based on Archard’s wear model. The prediction models estimated the passenger train of one set emits 6.6mg/km-train at 60m/s speed. The effects of train speed on the PM emission has been also investigated and resulted in when the train speed increase the metal PM emission decrease. Using the model the metal PM emission has been studied for the train line between Leeds and Manchester to show potential emissions produced each day. This PM emission characteristics can be used to monitor the brakes, the wheels and the rail tracks conditions in future

Insights in the cost of continuous broadband Internet on trains for multi-service deployments by multiple actors with resource sharing

The economic viability of broadband Internet services on trains has always been proved difficult, mainly due to a high investment cost and low willingness to pay by train passengers, but also due to unused opportunities such as non-passenger services (e.g. train performance monitoring, crew services) and optimization of the resources consumed to offer Internet services. Evaluating opportunities to improve the return on investment is therefore essential towards profitability of the business case. By efficiently sharing resources amongst services, costs can be pooled over several services in order to reduce the investment cost per service. Current techno-economic evaluation models are hard to apply to cost allocation in a multi-service deployment with multiple actors and resource sharing. We therefore propose a new evaluation model and apply it to a deployment of Internet services on trains. We start with a detailed analysis of the technical architecture required to provide Internet access on trains. For each component, we investigate the impact by the different services on resource consumption. The proposed techno-economic evaluation model is then applied in order to calculate the total cost and allocate the used and unused resources to the appropriate services. In a final step, we calculate the business case for each stakeholder involved in the offering of these services. This paper details the proposed model and reports on our findings for a multi-service deployment by multiple actors. Results show important benefits for the case that considers the application of resource sharing in a multi-service, multi-actor scenario and the proposed model produces insights in the contributors to the cost per service and the unused amount of a resource. In addition, ex-ante insights in the cost flows per involved actor are obtained and the model can easily be extended to include revenue flows to evaluate the profitability per actor. As a consequence, the proposed model should be considered to support and stimulate upcoming multi-actor investment decisions for Internet-based multi-service offerings on-board trains with resource sharing

Development of an efficient finite element model for the dynamic analysis of the train-bridge interaction

The design of high-speed railway bridges comprises a set of demands, from safety and serviceability aspects, to new types of equipment and construction solutions. In order to perform an accurate and realistic evaluation of the corresponding dynamic behavior, adequate analysis tools that take into account the complexity of the train-bridge system are required. These computational tools must be based on efficient algorithms to allow for the completion of detailed dynamic analyses in a reasonable amount of time. The classical methods of analysis may be unsatisfactory in the evaluation of the dynamic effects of the train-bridge system and fully assessment of the structural safety, track safety and passenger comfort. A direct and versatile technique for the simulation of the train-bridge interaction was implemented in the FEMIX code, which is a general purpose finite element computer program. The presented case study is an application of the proposed formulation, which proved to be very accurate and efficient

Location-based software modeling and analysis: Tropos-based approach

Abstract. The continuous growth of interest in mobile applications makes the concept of location essential to design and develop software systems. Location-based software is supposed to be able to monitor the surrounding location and choose accordingly the most appropriate behavior. In this paper, we propose a novel conceptual framework to model and analyze location-based software. We mainly focus on the social facets of locations adopting concepts such as actor, resource, and location-based behavior. Our approach is based on Tropos methodology and allows the analyst to elicit and model software requirements according to the different locations where the software will operate. We propose an extension of Tropos modeling and adapt its process to suit well with the development of location-based software. The proposed framework also includes automated analysis techniques to reason about the relation between location and location-based software.

Rail Privatisation: The Economic Theory

The purpose of this paper is to examine the relevance of economic theory to the rail privatisation proposals contained in the Railways Act 1993. After a review of the latest rail privatisation literature four major themes emerged: (1) Contestability and Barriers to Entry. (2) Franchising. (3) Vertical Integration. (4) Horizontal Integration. Following a short review of the rail privatisation proposals the paper presents each theme in the context of the proposals. In conclusion, we highlight a number of future issues which will require monitoring and research in the future. In particular, we identify a number of hypotheses, put forward by both those in favour and against the Government's proposals, that should be tested