Impacto das Chuvas no Tráfego Urbano: Um Estudo de Caso na BR-104 em Alagoas
Resumo
Este estudo investiga como a ocorrência de chuvas impacta o fluxo de veículos na rodovia BR-104, no trecho que cruza a cidade de Maceió, capital do estado de Alagoas. Analisamos dados de tráfego do Plano Nacional de Contagem de Tráfego e dados de precipitação do Instituto Nacional de Meteorologia, coletados entre janeiro e dezembro de 2022. Aplicamos regressão linear e análise do erro percentual médio (MPE) para avaliar a variação no tráfego em dias de chuva. Como resultado foi observado um aumento na quantidade de veículos de passeio e uma diminuição no volume de veículos de maior porte.Referências
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Datla, S., Sahu, P., Roh, H.-J., and Sharma, S. (2013). A comprehensive analysis of the association of highway traffic with winter weather conditions. Procedia - Social and Behavioral Sciences, 104:497–506.
Dhaliwal, S. S., Wu, X., Thai, J., and Jia, X. (2017). Effects of rain on freeway traffic in southern california. Transportation Research Record, 2616(1):69–80.
Dismuke, C. and Lindrooth, R. (2006). Ordinary least squares. Methods and designs for outcomes research, 93(1):93–104.
DNIT (2022). Plano nacional de contagem de tráfego - dados de 2022. [link]. Acesso em: 04 jun. 2025.
Giardini, F., Hadjidimitriou, N. S., Mamei, M., Bastardi, G., Codeluppi, N., and Pancotto, F. (2023). Using mobile phone data to map evacuation and displacement: a case study of the central italy earthquake. Scientific Reports, 13.
IBGE (2024). Instituto Brasileiro de Geografia e Estatística. [link]. Acesso em: 14 jul. 2025.
INMET (2022). Instituto nacional de meteorologia - dados históricos de precipitação. [link]. Acesso em: 04 jun. 2025.
Jia, Y., Wu, J., and Xu, M. (2017). Traffic flow prediction with rainfall impact using a deep learning method. Journal of Advanced Transportation, 2017.
McCrum-Gardner, E. (2008). Which is the correct statistical test to use? British Journal of Oral and Maxillofacial Surgery, 46(1):38–41.
Meneguette, R. I., De Grande, R., and Loureiro, A. (2018). Intelligent transport system in smart cities. Cham: Springer International Publishing.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., et al. (2011). Scikit-learn: Machine learning in python. the Journal of machine Learning research, 12:2825–2830.
Pillar, V. D. and Overbeck, G. E. (2024). Learning from a climate disaster: The catastrophic floods in southern brazil. Science, 385(6713):eadr8356.
Qi, Y., Zheng, Z., and Jia, D. (2020). Exploring the spatial-temporal relationship between rainfall and traffic flow: A case study of brisbane, australia. Sustainability (Switzerland), 12.
Wang, Y.-Q. and Luo, J. (2017). Study of rainfall impacts on freeway traffic flow characteristics. Transportation Research Procedia, 25:1533–1543. World Conference on Transport Research – WCTR 2016, Shanghai.
Yin, C., Xiong, Z., Chen, H., Wang, J., Cooper, D., and David, B. (2015). A literature survey on smart cities. Science China. Information Sciences, 58(10):1–18.
Publicado
12/08/2025
Como Citar
BRASILEIRO, Victor A. L.; RAMOS, Geymerson S.; AQUINO, Andre L. L..
Impacto das Chuvas no Tráfego Urbano: Um Estudo de Caso na BR-104 em Alagoas. In: ESCOLA REGIONAL DE COMPUTAÇÃO BAHIA, ALAGOAS E SERGIPE (ERBASE), 25. , 2025, Lagarto/SE.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 132-141.
DOI: https://doi.org/10.5753/erbase.2025.13651.
