A nested recursive logit model for route choice analysis

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 c...

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Bibliographic Details
Main Authors: MAI, Tien, FOSGERAU, Mogens, FREJINGER, Emma
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2015
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Online Access:https://ink.library.smu.edu.sg/sis_research/5288
https://ink.library.smu.edu.sg/context/sis_research/article/6291/viewcontent/1_s2.0_S0191261515000582_main.pdf
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Institution: Singapore Management University
Language: English
Description
Summary: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.