Neues verkehrswissenschaftliches Journal - Ausgabe 26

User-based Adaptable High Performance Simulation Modelling and Design for Railway Planning and Operations

Yong Cui

• Verlag: Books on Demand
• Jahr: 2018
• ISBN:
  9783748113164
• Auflage: 1
• Thema: Technology & Engineering
• Thema: Engineering General

Simulation methods are widely-used in the field of railway planning and operations. However, the various tools are all lacking with respect to the standards they utilise as well as their published interfaces. For an end-user, the basic mechanism and the assumptions built into a simulation tool are unknown, which means that the true potential of these software tools is limited. One of the most critical issues is the lack of the ability of users to define a sophisticated workflow, integrated in several rounds of simulation with adjustable parameters and settings. This book develops and describes a user-based, customisable platform. As the preconditions of the platform, the design aspects for modelling the components of a railway system and building the workflow of railway simulation are elaborated in detail. Based on the model and the workflow, an integrated simulation platform with open interfaces is developed. Users and researchers gain the ability to rapidly develop their own algorithms, supported by the tailored simulation process in a flexible manner. The productivity of using simulation tools for further evaluation and optimisation will be significantly improved through the user-adaptable open interfaces.

1 Basis of Railway Simulation Modelling and Design

1.1 Simulation for Railway Planning and Operations

During the process of railway planning and operations, the most common tasks are to study the relationships between infrastructure, rolling stocks and operations, and to predict the behaviour of the studied system. Based on the learned knowledge of the system, possible solutions to improve the efficiency and the quality of railway services can be derived. Each possible solution for railway planning and operations is called a design alternative. Different design alternatives will be investigated and evaluated through experiments. However, the cost of conducting these experiments on actual railway systems is too expensive and, at times, the studied system does not even exist. Therefore, it is not practical to examine the design alternatives upon an actual system directly.

A model can be built to represent the actual system for the sake of research at a low cost. The model can be either physical or mathematical (Law 2007). Some research institutions and railway companies have built physical models in their laboratories for a certain part of railway network. A physical model represents the operational situation intuitively. It can be used for experiments of different operation scenarios or for training purposes. However, one drawback in the use of physical models is their lack of flexibility to be adapted for various railway networks in different scales. Therefore, mathematical models are more often used to describe the structure and the behaviour of the studied system quantitatively. In a mathematical model with an analytical approach, the states of the system are derived directly through a set of mathematical equations. It is practical to use analytical approaches for a simple railway network with a limited numbers of train runs or a collection of various homogeneous parts of a network in a closed-form expression. For a large scale, in non-homogeneous networks with a considerably high density of train movements, an analytical approach is not applicable due to the high computational complexity required, as well as the lack of available algorithms to link the various homogeneous parts. In this case, the simulation approach can be applied to study the structure and the interaction of a complex railway system.

The process for railway planning and operations using the simulation approach contains several steps. As the basis, the components of railway systems are modelled according to a specific design alternative. A design alternative will be simulated as an experiment, from which the output will be recorded for further evaluation. The design alternatives can be further improved in order to optimise the system performance and the quality of railway service. In Figure 1-1, an iterative process including modelling, simulation, evaluation and optimisation through the simulation approach for railway planning and operations is demonstrated.

Figure 1-1: The process using the simulation approach for railway planning and operations

Today, simulation approaches are being used widely for railway planning and operations. For example, potential conflicts and resulting waiting time can be derived through timetable simulation (Luethi et al. 2005), (Radtke 2005). According to the simulated results, the path of trains and/or the sequence of trains can be adjusted in order to reduce hindrances among train runs. Furthermore, stochastic disturbances will be introduced into the simulation tool, so that the robustness and the stability of the timetable can be investigated (Radtke, Bendfeldt 2001). In capacity research, randomly generated timetables are simulated in order to evaluate system performance (Martin et al. 2011) and to identify bottlenecks (Martin et al. 2014). For rescheduling and dispatching, the simulation approach can be applied to generate a dispatching timetable for solving conflicts during railway operations (Cui 2010). The simulation approach can also be used as a test environment for innovative technologies. For example, the potentials of using European Train Control System (ETCS) are evaluated using the simulation approach in (Kogel et al. 2010).

1.2 Design Aspects of Simulation Approach and Simulation of Train Runs

The design of simulation approaches for railway planning and operations includes two aspects: modelling the components of the railway system and building the work-flow of railway simulation.

The structural perspective of railway simulation is taken into consideration in the modelling of the components of railway systems. Depending on the context, the term "model" may have many different meanings (e.g. the physical models, the mathematical models). Unless otherwise specified, the term "model" within this work refers to the modelling of the components of railway systems.

With the simulation approach for railway planning and operations, the modelled components of railway systems consist of:

• Infrastructure
• Rolling stocks
• Railway operations

The attributes and states of railway systems are modelled in the components respectively. The attributes describe the static information of railway system, e.g. the length of a track, the configuration of a train, as well as the scheduled departure time of a train run. The states refer to the dynamic information throughout the duration of railway operations, e.g. the aspect of a signal, the running dynamics of a train, and the delay of a train run. Normally, the components of infrastructure and rolling stocks can be constructed independently. However the model of railway operations depends on both factors.

The design of simulation workflow focuses on the behavioural perspective of railway simulation. The control flows, including starting, proceeding, and terminating a simulation process, are regulated by the simulation workflow. Moreover, the messages exchanged among infrastructure, rolling stocks, and railway operations are triggered inside the workflow. The model of a railway system and the simulation workflow can be designed independently. With a certain level of abstraction, the simulation work-flow can be designed without knowledge of the details of the underlying model.

After the design aspects for the components and the workflow are determined, the simulation of train runs can be started, which includes the simulation of each individual train run and simulation of multiple train runs. Each train run of a given operating program (see Section 2.4.2) will be simulated until it is accomplished. Driven by the concrete mechanism of a simulation workflow, the states of the modelled components of railway systems are changed. For example, the occupancy situation of infrastructure, the aspect of signals, and the position of trains are updated during a simulation process. The calculation of running dynamics and the signalling system are the basis for updating the states of components. The interaction between infrastructure and each individual train run, as well as the interaction among multiple train runs should be taken into consideration. The changed states of the components can be recorded for further evaluation and optimisation. The relationship between design aspects of the simulation approach and simulation of train runs is shown in Figure 1-2.

Figure 1-2: Design aspects of the simulation approach and simulation of train runs

1.3 Simulation Software for Railway Planning and Operation

Since the 1990s, serval simulation tools have been made available for railway planning and operations. Most of the tools were originally developed as experimental versions by railway research institutes and universities. Through continuous development and trial, these tools have become increasingly practical for research and commercial purposes. The user base of these tools consists of researchers, railway infrastructure companies, and railway operating companies.

In German-speaking countries and in Europe, the simulation software RailSys (by Rail Management Consultants GmbH, (RMCON 2010)), OpenTrack (by OpenTrack Railway Technology Ltd., (Hürlimann 2010)), and LUKS (by VIA Consulting & Development GmbH, (VIA Con 2011)) are very popular for railway planning and operations. These software tools provide not only the functionality for railway simulation, but also enable further evaluation and optimisation for scheduling, dispatching and capacity research. Thanks to the various applications and projects, a large amount of data of railway infrastructure, rolling stocks, and operations are now available.

However, the true potential of these software tools has not yet been sufficiently utilised. The standards and the published interfaces for the various tools are insufficient as well. For third party users and developers, it is difficult to understand the assumptions and simplifications within the used tools. Therefore, the analysis and the conclusion of a given set of simulation results can be weakened due to the lack of knowledge of the simulation tools themselves. In addition, the workload re...