Integrating driving and traffic simulators for the study of railway level crossing safety interventions: a methodology

Safety at Railway Level Crossings (RLXs) is an important issue within the Australian transport system. Crashes at RLXs involving road vehicles in Australia are estimated to cost $10 million each year. Such crashes are mainly due to human factors; unintentional errors contribute to 46% of all fatal collisions and are far more common than deliberate violations. This suggests that innovative intervention targeting drivers are particularly promising to improve RLX safety. In recent years there has been a rapid development of a variety of affordable technologies which can be used to increase driver’s risk awareness around crossings. To date, no research has evaluated the potential effects of such technologies at RLXs in terms of safety, traffic and acceptance of the technology. Integrating driving and traffic simulations is a safe and affordable approach for evaluating these effects. This methodology will be implemented in a driving simulator, where we recreated realistic driving scenario with typical road environments and realistic traffic. This paper presents a methodology for evaluating comprehensively potential benefits and negative effects of such interventions: this methodology evaluates driver awareness at RLXs , driver distraction and workload when using the technology . Subjective assessment on perceived usefulness and ease of use of the technology is obtained from standard questionnaires. Driving simulation will provide a model of driving behaviour at RLXs which will be used to estimate the effects of such new technology on a road network featuring RLX for different market penetrations using a traffic simulation. This methodology can assist in evaluating future safety interventions at RLXs

Efficient design assessment in the railway electric infrastructure domain using cloud computing

Nowadays, railway infrastructure designers rely heavily on computer simulators and expert systems to model, analyze and evaluate potential deployments prior to their installation. This paper presents the railway power consumption simulator model (RPCS), a cloud-based model for the design, simulation and evaluation of railway electric infrastructures. This model integrates the parameters of an infrastructure within a search engine that generates and evaluates a set of simulations to achieve optimal designs, according to a given set of objectives and restrictions. The knowledge of the domain is represented as an ontology that translates the elements in the infrastructure into an electric circuit, which is simulated to obtain a wide range of electric metrics. In order to support the execution of thousands of scenarios in a scalable, efficient and fault-tolerant manner, this paper introduces an architecture to deploy the model in a cloud environment, and a dimensioning model to find the types and number of instances that maximize performance while minimizing the externalization costs. The resulting model is applied to a particular case study, allowing the execution of over one thousand concurrent experiments in a virtual cluster on the Amazon Elastic Compute Cloud.This work has been partially funded under the grant TIN2013-41350-P of the Spanish Ministry of Economics and Competitiveness, and the COST Action IC1305 ”Network for Sustainable Ultrascale Computing Platforms” (NESUS)

Técnicas de altas prestaciones aplicadas al diseño de infraestructuras ferroviarias complejas

In this work we will focus on overhead air switches design problem. The design of railway infrastructures is an important problem in the railway world, non-optimal designs cause limitations in the train speed and, most important, malfunctions and breakages. Most railway companies have regulations for the design of these elements. Those regulations have been defined by the experience, but, as far as we know, there are no computerized software tools that assist with the task of designing and testing optimal solutions for overhead switches. The aim of this thesis is the design, implementation, and evaluation of a simulator that that facilitates the exploration of all possible solutions space, looking for the set of optimal solutions in the shortest time and at the lowest possible cost. Simulators are frequently used in the world of rail infrastructure. Many of them only focus on simulated scenarios predefined by the users, analyzing the feasibility or otherwise of the proposed design. Throughout this thesis, we will propose a framework to design a complete simulator that be able to propose, simulate and evaluate multiple solutions. This framework is based on four pillars: compromise between simulation accuracy and complexity, automatic generation of possible solutions (automatic exploration of the solution space), consideration of all the actors involved in the design process (standards, additional restrictions, etc.), and finally, the expert’s knowledge and integration of optimization metrics. Once we defined the framework different deployment proposes are presented, one to be run in a single node, and one in a distributed system. In the first paradigm, one thread per CPU available in the system is launched. All the simulators are designed around this paradigm of parallelism. The second simulation approach will be designed to be deploy in a cluster with several nodes, MPI will be used for that purpose. Finally, after the implementation of each of the approaches, we will proceed to evaluate the performance of each of them, carrying out a comparison of time and cost. Two examples of real scenarios will be used.El diseño de agujas aéreas es un problema bastante complejo y critico dentro del proceso de diseño de sistemas ferroviarios. Un diseño no óptimo puede provocar limitaciones en el servicio, como menor velocidad de tránsito, y lo que es más importante, puede ser la causa principal de accidentes y averías. La mayoría de las compañías ferroviarias disponen de regulaciones para el diseño correcto de estas agujas aéreas. Todas estas regulaciones han sido definidas bajo décadas de experiencia, pero hasta donde sé, no existen aplicaciones software que ayuden en la tarea de diseñar y probar soluciones óptimas. Es en este punto donde se centra el objetivo de la tesis, el diseño, implementación y evaluación de un simulador capaz de explorar todo el posible espacio de soluciones buscando el conjunto de soluciones óptimas en el menor tiempo y con el menor coste posible. Los simuladores son utilizados frecuentemente en el mundo de la infraestructura ferroviaria. Muchos de ellos solo se centran en la simulación de escenarios preestablecidos por el usuario, analizando la viabilidad o no del diseño propuesto. A lo largo de esta tesis, se propondrá un framework que permita al simulador final ser capaz de proponer, simular y evaluar múltiples soluciones. El framework se basa en 4 pilares fundamentales, compromiso entre precisión en la simulación y la complejidad del simulador; generación automática de posibles soluciones (exploración automática del espacio de soluciones), consideración de todos los agentes que intervienen en el proceso de diseño (normativa, restricciones adicionales, etc.) y por último, el conocimiento del experto y la integración de métricas de optimización. Una vez definido el framework se presentaran varias opciones de implementación del simulador, en la primera de ellas se diseñará e implementara una versión con hilos pura. Se lanzara un hilo por cada CPU disponible en el sistema. Todo el simulador se diseñará en torno a este paradigma de paralelismo. En un segundo simulador, se aplicará un paradigma mucho más pensado para su despliegue en un cluster y no en un único nodo (como el paradigma inicial), para ello se empleara MPI. Con esta versión se podrá adaptar el simulador al cluster en el que se va a ejecutar. Por último, se va a emplear un paradigma basado en cloud computing. Para ello, según las necesidades del escenario a simular, se emplearán más o menos máquinas virtuales. Finalmente, tras la implementación de cada uno de los simuladores, se procederá a evaluar el rendimiento de cada uno de ellos, realizando para ello una comparativa de tiempo y coste. Se empleara para ello dos ejemplos de escenarios reales.Programa Oficial de Doctorado en Ciencia y Tecnología InformáticaPresidente: José Daniel García Sánchez.- Secretario: Antonio García Dopico.- Vocal: Juan Carlos Díaz Martí

State of the Art of Virtual Reality Simulation Technology and Its Applications in 2005

The School of Mining Engineering at the University of New South Wales (UNSW) has been developing immersive, interactive computer-based training simulators for a number of years with research funding provided by Coal Services (CS), the Australian Coal Association Research Program (ACARP) and the Australian Research Council (ARC). The virtual reality(VR) simulators are being developed to improve the effectiveness of training in the Australian coal mining industry with a view to enhancing health and safety. VR theatres have been established at UNSW and at the Newcastle Mines Rescue Station (NMRS).A range of experienced and inexperienced mining personnel has already had the opportunity to train in them. A capability in immersive, interactive virtual reality training has been established and the reaction to the new technology has been positive and confirmed the benefits to be gained in going to the next stage in developing this capability. Given the significant advances in computer technology that have occurred since this research was initiated at UNSW, it was considered wise to undertake a study of the ‘State of the Art of Virtual Reality Simulation Technology and Its Application in 2005’. This should enable nformed decisions to be made on technologies and techniques that could further enhance the simulators and give insight into how the existing VR capability at UNSW can be placed on a sustainable foundation. This Research Overview summarises the findings of the study. It recommends the continued development and testing of the simulators towards a system that presents the users with hi-fidelity imagery and function that is based on 3D models, developed using real mine plans, safety data and manufacturer’s drawings. The simulators should remain modular in design, such that equipment can be updated and added easily over time. Different mine training scenarios and models based on sound educational principles should be developed with major input from experienced mining industry personnel. The simulations that have been developed, that is, Self-Escape, Rib Stability and Sprains and Strains should also continue to be developed and refined. The study has confirmed that such simulations are a powerful visualisation and training tool for enhancing the understanding of mine safety procedures and operations in the coal mining industry. This Scoping Study was undertaken with funding provided from the JCB Health and Safety Trust administered by Coal Services Pty Limited. The support of the Trust and trustees is gratefully acknowledged. The contributors of information are also gratefully acknowledged

Development of numerical and experimental tools for the simulation of train braking operations

L'abstract è presente nell'allegato / the abstract is in the attachmen

An Event-Based Synchronization Framework for Controller Hardware-in-the-loop Simulation of Electric Railway Power Electronics Systems

The Controller Hardware_in_the_loop (CHIL) simulation is gaining popularity as a cost_effective, efficient, and reliable tool in the design and development process of fast_growing electrified transportation power converters. However, it is challenging to implement the conventional CHIL simulations on the railway power converters with complex topologies and high switching frequencies due to strict real_time constraints. Therefore, this paper proposes an event-based synchronization CHIL (ES_CHIL) framework for high_fidelity simulation of these electrified railway power converters. Different from conventional CHIL simulations synchronized through the time axis, the ES_CHIL framework is synchronized through the event axis. Therefore, it can ease the real_time constraint and broaden the upper bound on the system size and switching frequency. Besides, models and algorithms with higher accuracy, such as the diode model with natural commutation processes, can be used in the ES-CHIL framework. The proposed framework is validated for a 350 kW wireless power transformer system containing 24 fully controlled devices and 36 diodes by comparing it with Simulink and physical experiments. This research improves the fidelity and application range of the power converters CHIL simulation. Thus, it helps to accelerate the prototype design and performance evaluation process for electrified railways and other applications with such complex converters

Dynamic Effects Increasing Network Vulnerability to Cascading Failures

We study cascading failures in networks using a dynamical flow model based on simple conservation and distribution laws to investigate the impact of transient dynamics caused by the rebalancing of loads after an initial network failure (triggering event). It is found that considering the flow dynamics may imply reduced network robustness compared to previous static overload failure models. This is due to the transient oscillations or overshooting in the loads, when the flow dynamics adjusts to the new (remaining) network structure. We obtain {\em upper} and {\em lower} limits to network robustness, and it is shown that {\it two} time scales $\tau$ and $\tau_0$, defined by the network dynamics, are important to consider prior to accurately addressing network robustness or vulnerability. The robustness of networks showing cascading failures is generally determined by a complex interplay between the network topology and flow dynamics, where the ratio $\chi=\tau/\tau_0$ determines the relative role of the two of them.Comment: 4 pages Latex, 4 figure

Adaptation, deployment and evaluation of a railway simulator in cloud environments

Many scientific areas make extensive use of computer simulations to study realworld processes. As they become more complex and resource-intensive, traditional programming paradigms running on supercomputers have shown to be limited by their hardware resources. The Cloud and its elastic nature has been increasingly seen as a valid alternative for simulation execution, as it aims to provide virtually infinite resources, thus unlimited scalability. In order to bene t from this, simulators must be adapted to this paradigm since cloud migration tends to add virtualization and communication overhead. This work has the main objective of migrating a power consumption railway simulator to the Cloud, with minimal impact in the original code and preserving performance. We propose a data-centric adaptation based in MapReduce to distribute the simulation load across several nodes while minimising data transmission. We deployed our solution on an Amazon EC2 virtual cluster and measured its performance. We did the same in in our local cluster to compare the solution's performance against the original application when the Cloud's overhead is not present. Our tests show that the resulting application is highly scalable and shows a better overall performance regarding the original simulator in both environments. This document summarises the author's work during the whole adaptation development process .Ingeniería Informátic

A cloudification methodology for multidimensional analysis: Implementation and application to a railway power simulator

Many scientific areas make extensive use of computer simulations to study complex real-world processes. These computations are typically very resource-intensive and present scalability issues as experiments get larger even in dedicated clusters, since these are limited by their own hardware resources. Cloud computing raises as an option to move forward into the ideal unlimited scalability by providing virtually infinite resources, yet applications must be adapted to this new paradigm. This process of converting and/or migrating an application and its data in order to make use of cloud computing is sometimes known as cloudifying the application. We propose a generalist cloudification method based in the MapReduce paradigm to migrate scientific simulations into the cloud to provide greater scalability. We analysed its viability by applying it to a real-world railway power consumption simulatior and running the resulting implementation on Hadoop YARN over Amazon EC2. Our tests show that the cloudified application is highly scalable and there is still a large margin to improve the theoretical model and its implementations, and also to extend it to a wider range of simulations. We also propose and evaluate a multidimensional analysis tool based on the cloudified application. It generates, executes and evaluates several experiments in parallel, for the same simulation kernel. The results we obtained indicate that out methodology is suitable for resource intensive simulations and multidimensional analysis, as it improves infrastructure’s utilization, efficiency and scalability when running many complex experiments.This work has been partially funded under the grant TIN2013-41350-P of the Spanish Ministry of Economics and Competitiveness, and the COST Action IC1305 "Network for Sustainable Ultrascale Computing Platforms" (NESUS)