Publication Type

Journal Article

Version

publishedVersion

Publication Date

5-2015

Abstract

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.

Keywords

Route choice modeling, Nested recursive logit, Substitution patterns, Value iterations, Maximum likelihood estimation, Cross-validation

Discipline

Databases and Information Systems | OS and Networks

Research Areas

Intelligent Systems and Optimization

Publication

Transportation Research Part B: Methodological

Volume

75

First Page

100

Last Page

112

ISSN

0191-2615

Identifier

10.1016/j.trb.2015.03.015

Publisher

Elsevier

Additional URL

https://doi.org/10.1016/j.trb.2015.03.015

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