Rail traffic vehicles and infrastructure

In the research area Vehicles and infrastructure, mathematical modelling is used, together with experimental methods and field measurements, to investigate how selected characteristics of the train track system affect the function and performance of the rail transport system.

The research work takes into account all subsystems of the infrastructure, including the line, contact and signal safety systems. The mechanical characteristics of the vehicles and infrastructure affect the outcome of the coupled vehicle-track system. For the evaluation of the outcome in the form of, for example, mechanical wear, passenger comfort or noise emissions from either, both must be included in the analysis. However, the movement of vehicles is also affected by the actions of the drivers based on their impression and experience of the layout of the track and the information given by the signalling system and the train control centre. The resulting driver behaviour affects in turn wear on both rolling stock and infrastructure.

In the research area Vehicles and infrastructure, simulation tools are being developed with the ability to model this complex dynamic interaction between vehicle and track, while taking into account the interaction between the train driver and the traffic centre. Efficient maintenance requires assistive tools to estimate the future maintenance needs of the infrastructure or vehicles as well as methods for monitoring their condition. Supporting this development, among other things by taking advantage of the opportunities of digitalisation in the form of machine learning, for example, is an important task for VTI's research activities. The work is also closely linked to issues concerning how track systems should be designed and maintained with regard to socio-economic efficiency and life cycle costs.

Research areas

Our research areas in vehicles and infrastructure:

  • The track superstructure’s physical design, properties and ability to withstand degradation
  • Condition monitoring and maintenance planning
  • Dynamic train-track interaction
  • Development of train driver simulators

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