Bibliographic citations
Ibañez, M., Quindano, C. (2023). Evaluación comparativa de la tasa de flujo de saturación en las intersecciones semaforizadas de la Av. Martinelli utilizando las metodologías HCM 2010 y HCM 2016, provincia de Andahuaylas, región Apurímac 2023 [Universidad Andina del Cusco]. https://hdl.handle.net/20.500.12557/5936
Ibañez, M., Quindano, C. Evaluación comparativa de la tasa de flujo de saturación en las intersecciones semaforizadas de la Av. Martinelli utilizando las metodologías HCM 2010 y HCM 2016, provincia de Andahuaylas, región Apurímac 2023 []. PE: Universidad Andina del Cusco; 2023. https://hdl.handle.net/20.500.12557/5936
@misc{renati/956132,
title = "Evaluación comparativa de la tasa de flujo de saturación en las intersecciones semaforizadas de la Av. Martinelli utilizando las metodologías HCM 2010 y HCM 2016, provincia de Andahuaylas, región Apurímac 2023",
author = "Quindano Larrea, Cristabel Frida",
publisher = "Universidad Andina del Cusco",
year = "2023"
}
This thesis focuses on the field of Traffic Engineering, specifically studying the signalized intersections of Martinelli Avenue in the city of Andahuaylas, located in the Apurímac region. Martinelli Avenue is a tertiary road that connects the national road network and is characterized by traffic flow conflicts due to intense commercial activity, a significant presence of pedestrians, schools, and other entities in the analysis area. The absence of an optimal traffic management system on Martinelli Avenue has led to continuous delays, impeding traffic flow. Given that this avenue experiences higher traffic volumes compared to other roads in a smaller city, there is a need to conduct a comparative analysis of saturation flow rates using the HCM 2010 and HCM 2016 methodologies. The aim is to provide the population with an optimal understanding of saturation flow rates and delays at the signalized intersections of Martinelli Avenue. This study will employ the HCM 2010 and HCM 2016 methodologies to determine the base saturation flow rates at the intersections of Martinelli Avenue. The results will be tailored to the specific conditions of this road, taking into account factors such as commercial intensity, pedestrian presence, and existing infrastructure. By conducting a comparative analysis of the two methodologies, we seek to evaluate which one provides a more accurate estimation of saturation flow rates at these intersections. This study will contribute to a better understanding of current traffic conditions on Martinelli Avenue and potentially offer valuable insights for proposing improvements to reduce delays and optimize traffic flow at these signalized intersections.
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