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A review of Machine Learning (ML) algorithms used for modeling travel mode choice
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Journal Article
A review of Machine Learning (ML) algorithms used for modeling travel mode choice
2019
Overview
In recent decades, transportation planning researchers have used diverse types of machine learning (ML) algorithms to research a wide
range of topics. This review paper starts with a brief explanation of some ML algorithms commonly used for transportation research,
specifically Artificial Neural Networks (ANN), Decision Trees (DT), Support Vector Machines (SVM) and Cluster Analysis (CA). Then,
these different methodologies used by researchers for modeling travel mode choice are collected and compared with the Multinomial Logit
Model (MNL) which is the most commonly-used discrete choice model. Finally, the characterization of ML algorithms is discussed and
Random Forest (RF), a variant of Decision Tree algorithms, is presented as the best methodology for modeling travel mode choice.
En décadas recientes, los investigadores de planificación de transporte han usado diversos tipos de algoritmos de Machine Learning (ML,
por sus siglas en inglés) para investigar un amplio rango de temas. Este artículo de revisión inicia con una breve explicación de algunos
algoritmos de Machine Learning comúnmente utilizados para la investigación en transporte, específicamente Redes Neuronales Artificiales
(ANN), Árboles de Decisión (DT), Máquinas de Vector de Soporte (SVM) y Análisis de Grupos (CA). Luego, estas diferentes metodologías
usadas por investigadores para modelar la elección de modo de viaje son recogidos y comparados con el Modelo Logit Multinomial (MNL)
el cual es el modelo de elección discreta más comúnmente utilizado. Finalmente, la caracterización de los algoritmos de ML es discutida y
el Bosque Aleatorio (RF), una variante de los algoritmos de Árboles de Decisión, es presentado como la mejor metodología para modelar
la elección de modo de viaje
Subject
algoritmos de Machine Learning (ML)
/ Artificial Neural Networks (ANN)
/ Machine Learning (ML) algorithms
/ modelación de la elección de modo de viaje
/ Modelo Logit Multinomial (MNL)
/ Multinomial Logit Model (MNL)
/ Máquinas de Vector de Soporte (SVM)
/ Redes Neuronales Artificiales (ANN)
/ Support
