A nested recursive logit model for route choice analysis

Tien Mai, Emma Frejinger, Mogens Fosgerau

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    We propose a route choice model that relaxes the independence from irrelevant alternatives property of the logit model by allowing scale parameters to be link specific. Similar to the recursive logit (RL) model proposed by Fosgerau et al. (2013), the choice of path is modeled as a sequence of link choices and the model does not require any sampling of choice sets. Furthermore, the model can be consistently estimated and efficiently used for prediction.A key challenge lies in the computation of the value functions, i.e. the expected maximum utility from any position in the network to a destination. The value functions are the solution to a system of non-linear equations. We propose an iterative method with dynamic accuracy that allows to efficiently solve these systems.We report estimation results and a cross-validation study for a real network. The results show that the NRL model yields sensible parameter estimates and the fit is significantly better than the RL model. Moreover, the NRL model outperforms the RL model in terms of prediction.
    Original languageEnglish
    JournalTransportation Research Part B: Methodological
    Pages (from-to)100-112
    Number of pages13
    Publication statusPublished - 2015


    • Route choice modeling
    • Nested recursive logit
    • Substitution patterns
    • Value iterations
    • Maximum likelihood estimation
    • Cross-validation
    • Iterative methods
    • Maximum likelihood
    • Cross validation
    • Route choice model
    • Value iteration

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