Towards automated model calibration and validation in rail transit simulation

The benefit of modeling and simulation in rail transit operations has been demonstrated in various studies. However, the complex dynamics involved and the ever-changing environment in which rail systems evolve expose the limits of classical simulation. Changing environmental conditions and second order dynamics challenge the validity of the models and seriously reduce model (re-)usability. This paper discusses the potential benefits and requirements of dynamic data-driven simulation in rail systems. The emphasis is placed on automated model reconfiguration, calibration, and validation through the use of data analysis methods. The rationale and requirements are discussed and a process model for data driven calibration and validation is proposed.