Choice probabilities and correlations in closed-form route choice models: specifications and drawbacks

TL;DR

This paper evaluates various closed-form route choice models, comparing their ability to replicate choice probabilities and correlations, and introduces improvements for better practical application.

Contribution

It introduces new specifications of the CoNL model and provides practical guidance for modeling correlations in route choice analysis.

Findings

CoNL models best fit MNP correlations and probabilities

Introducing lower bounds to nesting parameters improves model performance

Models with limited correlation coverage perform poorly

Abstract

This paper investigates the performance, in terms of choice probabilities and correlations, of existing and new specifications of closed-form route choice models with flexible correlation patterns, namely the Link Nested Logit (LNL), the Paired Combinatorial Logit (PCL) and the more recent Combination of Nested Logit (CoNL) models. Following a consolidated track in the literature, choice probabilities and correlations of the Multinomial Probit (MNP) model by (Daganzo and Sheffi, 1977) are taken as target. Laboratory experiments on small/medium-size networks are illustrated, also leveraging a procedure for practical calculation of correlations of any GEV models, proposed by (Marzano 2014). Results show that models with inherent limitations in the coverage of the domain of feasible correlations yield unsatisfactory performance, whilst the specifications of the CoNL proposed in the paper appear the best in fitting both MNP correlations and probabilities. Performance of the models are appreciably ameliorated by introducing lower bounds to the nesting parameters. Overall, the paper provides guidance for the practical application of tested models.