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This paper focuses on the application of tractable route choice models and presents a set of methods for deriving relevant disaggregate and aggregate route choice indicators, namely link and route flows. Tractability is achieved at the disaggregate level by the recursive logit model and at the aggregate level by the mental representation item (\(\mathrm {MRI}\)) approach. These two approaches are analyzed here, and extensions of the \({\mathrm {MRI}}\) approach are presented. The analysis elaborates on the features of each model and allows to draw insights into the use of a specific model, depending on the needs of the application and the data availability. The performance of the two models is tested on real data. The results demonstrate the validity of the \({\mathrm {MRI}}\) model that is intended for aggregate analysis.

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