Validation of a Public Transport Model

University essay from KTH/Optimeringslära och systemteori

Abstract: During 2018, the Public Transport Administration (Trafikförvaltningen) in the Stockholm region spent approximately 2.2 billion SEK on new infrastructure investments related to the public transport system, many of which were based on their public transport models. The previously used method for validating these models has lacked scientific rigour, efficiency and a systematic approach, which has led to uncertainty in decision making. Furthermore, few scientific studies have been conducted to develop validation methodologies for large-scale models, such as public transport models. For these reasons, a scientific validation methodology for public transport models has been developed in this thesis. This validation methodology has been applied on the 2014 route assignment model used by Trafikförvaltningen, for the transport modes bus, commuter train and local tram. In the developed validation methodology, the selected validation metrics called MAPE, %RMSE and R^2 are used to compare link loads from a route assignment model with observed link loads from an Automatic Passenger Counting (APC) system. To obtain an overview of the performance of the route assignment model, eight different scenarios are set, based on whether the validation metrics meet acceptable thresholds or not. In the application of the developed validation methodology, the average link loads for the morning rush have been validated. To adjust the developed validation methodology to system-specific factors and to set acceptable metric thresholds, discussions with model practitioners have taken place. The validation has been performed on both lines and links, and for bus entire line number series have been validated as well. The validation results show that commuter train meets the set threshold values in a higher proportion than bus and local tram do. However, Trafikförvaltningen is recommended to further calibrate the route assignment model in order to achieve a better model performance. The developed validation methodology can be used for validation of public transport models, and can in combination with model calibration be used in an iterative process to fine-tune model parameters for optimising validation results. Finally, a number of recommendations are proposed for Trafikförvaltningen to increase the efficiency and quality of the validation process, such as synchronising model data with the observed data.

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