TraffSim

A complex mathematical model for the analytical simulation of input and revenue data for public transport services.

R&D project by Corvex AG, our development partner

The aim of the Traffsim project

Create a complex simulation model and its application environment that can be used for the structured use of static and dynamic data taken from public transport and its environment, from the material level system. Describe the processes of the desired transport system, taking into account the technical aspects of economic and transport-technical and information flow. In the course of modelling, we use input data: topographical, traffic, human, technical, economic and other external data. In the course of the research, we wish to define a model and simulation system and to create it as a result of the development, the application of which to the resources used by the system to be investigated. 

At the service level, transport can be asked professional questions and the answers supported by the calculations can be used to optimise the operation of the transport system. These areas of optimisation, in addition to the TCO-based economic area, also affect other areas specific to the profession (traffic, engineering, human). Therefore, the model may also be suitable for testing the impact of new innovative technologies. The fundamental question is how the changes that occur or are being made in certain elements of the transport system have an impact, for example. the quality of service, the concept defined by the increasingly SLA.

Research and development work basically focuses on two areas

1.

Modelling the real system to be investigated (defined subsystems of public transport) with mathematical algorithms and IT tools. That is the creation of the model itself.

2.

Functional simulation of the model thus created. That is, how the model is working, how accurate it is to describe the subject of the investigation. However, this is only a verification function because the real question is what kind of answers the simulation system gives to the data within the given range of interpretation.

With the product to be implemented in the TraffSim research and development project, we develop a tool that will be available to the transport industry, which will allow for the examination of existing transport (sub) systems and the future (abstraction) of non-existing transport service elements. It also examines how it works.

Process-oriented modelling

  • Traffic submodel creation
  • Economic sub-model creation
  • Human submodel Creation (Social Impact)
  • Technical sub-model creation
  • Integration of the above sub-models (1-4) into a common system

Data-oriented modelling

Data model concept

  • measured data
  • calculated data
  • know how data (knowledge-based data)
  • hypothetical data

Data model creation

  • logical data model
  • physical data model

The research carried out in the TraffSim project is a new professional field, because it aims to create a comprehensive model (integrating all the elements of the system to be examined) from a transport, technical, human, economic or complex point of view. This means that the model also provides an opportunity to apply one or more complex interpretations of the examined one, according to the purpose of the study. The project defines public transport as a multi-dimensional problem space, its operating costs and revenues in this field are mathematical functions interpreted in this field. On the basis of real and trained data, mathematical methods applied in this space simulate public transport and produce transitions. The area we are looking for is the lines that make up the system (vehicles) or the system. through the examination of their entities, it creates a complex modelling and theory in the field of public transport. As a result, the boundaries of scientific knowledge and test areas are significantly extended to the study of complex systems. 

Key functionalities of TraffSim –
we create scientific value

  • arbitrary selection of the scope of the test

  • selection of test criteria (inputs) tailored to the test purpose

  • dynamic correlation analysis between input and output data

  • database training and self-learning

  • bottom-up or detailed top-down implementation from full to detail

As a result of the research and development project, we get possession of a process that can demonstrate its functioning and the expected impact of given measures by approaching it with the iteration of the real relations without interfering with the material-energy system (ie. without disturbing it). As a first step, we determine the scope of the test system boundaries. Methodological basis: in the research of the model and the simulation procedure, we use the system creation composition/decomposition methodology. This means that we see the simulation system we create as a model as a set of relationships between the entities that make it and the entities. From this system of relationships, the relevant process elements that are the set of processes to be investigated (transport system) are selected by systematic method (based on the main component and independent component analysis) and therefore relevant to the model. Our research work hypothesis is that it is possible to define entities that describe the transport system (base unit) that represent the model’s parameters, and can be examined as a dimension by using the available IT resources.

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