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Latent variables and route choice behavior

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Abstract

In the last decade, a broad array of disciplines has shown a general interest in enhancing discrete choice models by considering the incorporation of psychological factors affecting decision making. This paper provides insight into the comprehension of the determinants of route choice behavior by proposing and estimating a hybrid model that integrates latent variable and route choice models. Data contain information about latent variable indicators and chosen routes of travelers driving regularly from home to work in an urban network. Choice sets include alternative routes generated with a branch and bound algorithm. A hybrid model consists of measurement equations, which relate latent variables to measurement indicators and utilities to choice indicators, and structural equations, which link travelers’ observable characteristics to latent variables and explanatory variables to utilities. Estimation results illustrate that considering latent variables (i.e., memory, habit, familiarity, spatial ability, time saving skills) alongside traditional variables (e.g., travel time, distance, congestion level) enriches the comprehension of route choice behavior.

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Acknowledgments

The authors would like to express their gratitude to Kay Axhausen and Michel Bierlaire for commenting on a preliminary version of the paper and suggesting improvements to the model specification. The authors would also like to express their appreciation for the contribution of four anonymous reviewers.

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Correspondence to Carlo Giacomo Prato.

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Prato, C.G., Bekhor, S. & Pronello, C. Latent variables and route choice behavior. Transportation 39, 299–319 (2012). https://doi.org/10.1007/s11116-011-9344-y

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