Model of State Spaces for Estimating the Dynamic Origin–Destination Matrix for a Public Transport Network by Applying the Kalman Filter

Lina Patricia Zapata, Victor Manuel Larios, Francisco Castro Carrasco, José Luis Aguayo

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución de conferenciarevisión exhaustiva

Resumen

A model to estimate the passenger flow based on the dynamic origin–destination matrix applied at the South-Eastern Corridor from the terrestrial transport network in the city of Quito was the goal of this project. In the model, first: The state space was defined for the transport network, and later, was applied the Kalman Filter algorithm to get the dynamic origin–destination matrix. The state variables defined were the origin–destination pairs, the temporal variation, and the speed changes in the origin–destination pairs. Finally, the measure vector, the evolution matrix model, the process noise matrix, and the measurement error matrix were developed.

Idioma originalInglés
Título de la publicación alojadaCommunication, Smart Technologies and Innovation for Society - Proceedings of CITIS 2021
EditoresÁlvaro Rocha, Paulo Carlos López-López, Juan Pablo Salgado-Guerrero
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas117-128
Número de páginas12
ISBN (versión impresa)9789811641251
DOI
EstadoPublicada - 2022
Evento7th International Conference on Science, Technology and Innovation for Society, CITIS 2021 - Virtual, Online
Duración: 26 may. 202128 may. 2021

Serie de la publicación

NombreSmart Innovation, Systems and Technologies
Volumen252
ISSN (versión impresa)2190-3018
ISSN (versión digital)2190-3026

Conferencia

Conferencia7th International Conference on Science, Technology and Innovation for Society, CITIS 2021
CiudadVirtual, Online
Período26/05/2128/05/21

Nota bibliográfica

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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