Predicting modal choice for urban transport using an algebraic equation
Demand estimation and forecasting is an essential step in urban passenger transport planning. Relating the factors that influence the modal choice behavior of individuals facilitates demand estimation. In this study, we develop machine learning models that consider individuals' demographic, soc...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-11-01
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| Series: | Transportation Research Interdisciplinary Perspectives |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S259019822300194X |
| _version_ | 1797390394060701696 |
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| author | José E. Leal Victor Parada |
| author_facet | José E. Leal Victor Parada |
| author_sort | José E. Leal |
| collection | DOAJ |
| description | Demand estimation and forecasting is an essential step in urban passenger transport planning. Relating the factors that influence the modal choice behavior of individuals facilitates demand estimation. In this study, we develop machine learning models that consider individuals' demographic, socioeconomic, and travel characteristics to justify their mode choice. Two datasets are used to train and validate the models. We use logistic regression and multilayer perceptron models to classify public or private transportation trips. It was observed that a multilayer perceptron model with a low number of parameters could predict modal selection with an accuracy exceeding 90%. We derive an algebraic equation from this result to perform modal selection prediction. Our results show that the models can effectively predict the mode of transportation of individuals based on their demographic and travel characteristics. |
| first_indexed | 2024-03-08T23:11:05Z |
| format | Article |
| id | doaj.art-0f5f64795c5d41a8a29960407dbb099a |
| institution | Directory Open Access Journal |
| issn | 2590-1982 |
| language | English |
| last_indexed | 2024-03-08T23:11:05Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Transportation Research Interdisciplinary Perspectives |
| spelling | doaj.art-0f5f64795c5d41a8a29960407dbb099a2023-12-15T07:25:40ZengElsevierTransportation Research Interdisciplinary Perspectives2590-19822023-11-0122100947Predicting modal choice for urban transport using an algebraic equationJosé E. Leal0Victor Parada1Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, 55 Paulo VI Street, Rio de Janeiro, BrazilDepartment of Informatics Engineering, Universidad of Santiago of Chile & Instituto Sistemas Complejos de Ingeniería (ISCI), 3659 Ecuador Ave., Santiago, Chile; Corresponding author.Demand estimation and forecasting is an essential step in urban passenger transport planning. Relating the factors that influence the modal choice behavior of individuals facilitates demand estimation. In this study, we develop machine learning models that consider individuals' demographic, socioeconomic, and travel characteristics to justify their mode choice. Two datasets are used to train and validate the models. We use logistic regression and multilayer perceptron models to classify public or private transportation trips. It was observed that a multilayer perceptron model with a low number of parameters could predict modal selection with an accuracy exceeding 90%. We derive an algebraic equation from this result to perform modal selection prediction. Our results show that the models can effectively predict the mode of transportation of individuals based on their demographic and travel characteristics.http://www.sciencedirect.com/science/article/pii/S259019822300194XModal choiceMachine learningTransportation demand |
| spellingShingle | José E. Leal Victor Parada Predicting modal choice for urban transport using an algebraic equation Transportation Research Interdisciplinary Perspectives Modal choice Machine learning Transportation demand |
| title | Predicting modal choice for urban transport using an algebraic equation |
| title_full | Predicting modal choice for urban transport using an algebraic equation |
| title_fullStr | Predicting modal choice for urban transport using an algebraic equation |
| title_full_unstemmed | Predicting modal choice for urban transport using an algebraic equation |
| title_short | Predicting modal choice for urban transport using an algebraic equation |
| title_sort | predicting modal choice for urban transport using an algebraic equation |
| topic | Modal choice Machine learning Transportation demand |
| url | http://www.sciencedirect.com/science/article/pii/S259019822300194X |
| work_keys_str_mv | AT joseeleal predictingmodalchoiceforurbantransportusinganalgebraicequation AT victorparada predictingmodalchoiceforurbantransportusinganalgebraicequation |