Simulation analysis of school road traffic characteristics

Huasheng Liu; Haoran Deng; Jin Li; Yuqi Zhao; Sha Yang

doi:10.15446/dyna.v91n231.109853

Publicado

2024-01-31

Simulation analysis of school road traffic characteristics

Análisis de simulación de las características del tráfico escolar

DOI:

https://doi.org/10.15446/dyna.v91n231.109853

Palabras clave:

urban traffic; traffic characteristic; simulation analysis; sensitivity analysis; school commuting (en)
tráfico urbano; características del tráfico; análisis de simulación; análisis de sensibilidad; transporte escolar (es)

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Autores/as

Huasheng Liu Department of Transportation Planning and Management, Jilin University, Institute of Transportation, Chang Chun, China https://orcid.org/0000-0002-2635-999X
Haoran Deng Department of Transportation Planning and Management, Jilin University, Institute of Transportation, Chang Chun, China https://orcid.org/0009-0009-7463-830X
Jin Li Department of Transportation Planning and Management, Jilin University, Institute of Transportation, Chang Chun, China https://orcid.org/0000-0001-8783-4881
Yuqi Zhao Department of Transportation Planning and Management, Jilin University, Institute of Transportation, Chang Chun, China https://orcid.org/0009-0005-6952-8051
Sha Yang Department of Transportation Planning and Management, Jilin University, Institute of Transportation, Chang Chun, China https://orcid.org/0009-0006-9142-5435

Resumen (en)
Resumen (es)

This study aims to identify key factors and sensitive intervals affect the school road traffic characteristics. We collect traffic data from the parking area and the school road (400-700 meters). The simulation is calibrated to ensure the error of outputs are within 1.5%. A sensitivity analysis method is proposed, it makes the multifactor comparable. The sensitivity factors of vehicle delay, queue length, and average speed are 1.44, 2.03, and 0.28 in school road, and the bottleneck road are 3.07, 4.44, and 0.65. The traffic indicators change more concentrated in bottleneck road but greater in school road. 6 scenarios are created to analyze school road traffic characteristics. Traffic flow (TF), number of parking spaces (NPS), and stopping time (ST) are selected as variables. Scenarios 1-3 are univariate, and scenarios 4-6 are bivariate. TF is the key factor with a sensitivity interval of [1300,1700].

El objetivo de este estudio es identificar los factores clave y las zonas sensibles que afectan a las características del tráfico de las carreteras escolares. Recogemos datos de tráfico de la zona de aparcamiento y de la carretera escolar (400-700 metros). La simulación se calibró y el error de salida se situó dentro del 1,5%. Se propone un enfoque de análisis de sensibilidad multifactorial. Los coeficientes de sensibilidad para el retraso de los vehículos, la longitud de las colas y la velocidad media son 1,44, 2,03 y 0,28 para la sección de los colegios y 3,07, 4,44 y 0,65 para la sección de los cuellos de botella. Las variables son el flujo de tráfico (TF), el número de plazas de aparcamiento (NPS) y el tiempo de parada (ST). Los escenarios 1-3 y 4-6 se establecieron como univariantes y bivariantes.TF fue el factor clave con un intervalo de sensibilidad de [1300,1700].

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Cómo citar

IEEE

[1]

H. Liu, H. Deng, J. Li, Y. Zhao, y S. Yang, «Simulation analysis of school road traffic characteristics», DYNA, vol. 91, n.º 231, pp. 37–46, ene. 2024.

ACM

[1]

Liu, H., Deng, H., Li, J., Zhao, Y. y Yang, S. 2024. Simulation analysis of school road traffic characteristics. DYNA. 91, 231 (ene. 2024), 37–46. DOI:https://doi.org/10.15446/dyna.v91n231.109853.

ACS

(1)

Liu, H.; Deng, H.; Li, J.; Zhao, Y.; Yang, S. Simulation analysis of school road traffic characteristics. DYNA 2024, 91, 37-46.

APA

Liu, H., Deng, H., Li, J., Zhao, Y. & Yang, S. (2024). Simulation analysis of school road traffic characteristics. DYNA, 91(231), 37–46. https://doi.org/10.15446/dyna.v91n231.109853

ABNT

LIU, H.; DENG, H.; LI, J.; ZHAO, Y.; YANG, S. Simulation analysis of school road traffic characteristics. DYNA, [S. l.], v. 91, n. 231, p. 37–46, 2024. DOI: 10.15446/dyna.v91n231.109853. Disponível em: https://revistas.unal.edu.co/index.php/dyna/article/view/109853. Acesso em: 23 mar. 2026.

Chicago

Liu, Huasheng, Haoran Deng, Jin Li, Yuqi Zhao, y Sha Yang. 2024. «Simulation analysis of school road traffic characteristics». DYNA 91 (231):37-46. https://doi.org/10.15446/dyna.v91n231.109853.

Harvard

Liu, H., Deng, H., Li, J., Zhao, Y. y Yang, S. (2024) «Simulation analysis of school road traffic characteristics», DYNA, 91(231), pp. 37–46. doi: 10.15446/dyna.v91n231.109853.

MLA

Liu, H., H. Deng, J. Li, Y. Zhao, y S. Yang. «Simulation analysis of school road traffic characteristics». DYNA, vol. 91, n.º 231, enero de 2024, pp. 37-46, doi:10.15446/dyna.v91n231.109853.

Turabian

Liu, Huasheng, Haoran Deng, Jin Li, Yuqi Zhao, y Sha Yang. «Simulation analysis of school road traffic characteristics». DYNA 91, no. 231 (enero 24, 2024): 37–46. Accedido marzo 23, 2026. https://revistas.unal.edu.co/index.php/dyna/article/view/109853.

Vancouver

1.

Liu H, Deng H, Li J, Zhao Y, Yang S. Simulation analysis of school road traffic characteristics. DYNA [Internet]. 24 de enero de 2024 [citado 23 de marzo de 2026];91(231):37-46. Disponible en: https://revistas.unal.edu.co/index.php/dyna/article/view/109853

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CrossRef Cited-by

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1. Xiaojian Hu, Haoran Deng, Huasheng Liu, Jiayi Zhou, Hongyu Liang, Long Chen, Li Zhang. (2025). Assessment of the collision risk on the road around schools during morning peak period. Accident Analysis & Prevention, 210, p.107854. https://doi.org/10.1016/j.aap.2024.107854.

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