Calibração da relação fundamental do tráfego a partir de bases de dados muito grandes

Autores

  • Juliana Mitsuyama Cardoso Universidade de São Paulo
  • Lucas Assirati São Carlos School of Engineering, São Paulo – Brazil
  • José Reynaldo Setti São Carlos School of Engineering, São Paulo – Brazil https://orcid.org/0000-0003-3738-5605

DOI:

https://doi.org/10.14295/transportes.v29i1.2317

Palavras-chave:

Modelos de correntes de tráfego, Bases de dados muito grandes, Ajuste de modelos, Algoritmo genético

Resumo

Neste artigo, descreve-se um procedimento para ajustar modelos de correntes de tráfego a partir de bases de dados muito grandes. O procedimento proposto consiste em quatro etapas: (1) um tratamento inicial nos dados para eliminar observações espúrias (ruído) e homogeneizar a informação ao longo de toda a gama de densidades observada; (2) um ajuste inicial do modelo, baseado na soma dos erros quadráticos ortogonais; (3) uma segunda filtragem de dados, visando eliminar os outliers que sobreviveram ao tratamento inicial para eliminação do ruído; e (4) um segundo ajuste final do modelo. O método proposto foi testado ajustando-se o modelo de correntes de tráfego de Van Aerde a um conjunto de 104 mil observações coletadas por uma estação permanente de monitoramento de tráfego instalada numa autoestrada na região metropolitana de São Paulo. A calibração do modelo usou um algoritmo genético para procurar os melhores valores dos parâmetros do modelo. Os resultados obtidos demonstram a eficiência do método proposto.

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Publicado

2021-04-30

Como Citar

Mitsuyama Cardoso, J., Assirati, L., & Setti, J. R. (2021). Calibração da relação fundamental do tráfego a partir de bases de dados muito grandes. TRANSPORTES, 29(1), 212–228. https://doi.org/10.14295/transportes.v29i1.2317

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