Print Email Facebook Twitter A Literature Review on Train Motion Model Calibration Title A Literature Review on Train Motion Model Calibration Author Cunillera, A. (TU Delft Transport and Planning) Bešinović, Nikola (TU Delft Transport and Planning; Technische Universität Dresden) Lentink, Ramon M. (Nederlandse Spoorwegen) van Oort, N. (TU Delft Transport and Planning) Goverde, R.M.P. (TU Delft Transport and Planning) Date 2023 Abstract The dynamics of a moving train are usually described by means of a motion model based on Newton's second law. This model uses as input track geometry data and train characteristics like mass, the parameters that model the running resistance, the maximum tractive effort and power, and the brake rates to be applied. It can reproduce and predict train dynamics accurately if the mentioned train characteristics are carefully calibrated. The model constitutes the core element of a broad variety of railway applications, from timetabling tools to Driver Advisory Systems and Automatic Train Operation. Among the existing train motion model calibration techniques, those that use operational data are of particular interest, as they benefit from on- board recorded data, capturing the train dynamics during operation. In this literature review article we provide an overview of the train motion model calibration techniques that have been published in the scientific literature between January 2000 and December 2021 and either use operational data or can be minimally adapted to use it. To this end, we present a critical overview of the existing train motion model calibration approaches, distinguishing online calibration that analyzes data on- the-go and offline calibration that analyzes historical data batchwise. We propose a research agenda and highlight some potential goals to be tackled in the near future: from devising accurate online calibrators for eco-driving applications to quantitizing the physical sources of parameter variation. Last, we discuss practical recommendations for practitioners and scholars inferred from the current state of the art. Subject CalibrationComputational modelingmodel calibrationparameter estimationparameter identificationRail transportationrailwaysResistanceTrackingTrain motion modelTrajectoryvehicle dynamicsWheels To reference this document use: http://resolver.tudelft.nl/uuid:f21de50a-a351-41d6-84b2-25f8c323aa64 DOI https://doi.org/10.1109/TITS.2023.3236062 ISSN 1524-9050 Source IEEE Transactions on Intelligent Transportation Systems, 24 (4), 3660-3677 Part of collection Institutional Repository Document type journal article Rights © 2023 A. Cunillera, Nikola Bešinović, Ramon M. Lentink, N. van Oort, R.M.P. Goverde Files PDF A_Literature_Review_on_Tr ... ration.pdf 2.32 MB Close viewer /islandora/object/uuid:f21de50a-a351-41d6-84b2-25f8c323aa64/datastream/OBJ/view