Estudio de trafico de la Avenida Bolívar Madero Vargas entre cuarta norte y séptima norte. caso de estudio generación y atracción de viajes de YILPORT

Abstract

Abstract:This research addresses the problem of vehicular traffic on Bolívar Madero Vargas Avenue, the main access road to the YILPORT port in Puerto Bolívar. This road experiences high congestion due to the large influx of heavy transport linked to the export of products such as bananas, cocoa, and shrimp. YILPORT, as a high-demand multipurpose terminal, has created a traffic bottleneck that affects local traffic, especially during rush hour. The study is based on the need to plan logistics strategies that improve mobility and reduce the impact of heavy traffic. A logistics platform has been established in the fourth and seventh northern sectors of Puerto Bolívar to support the country's ports and customs, but there are still road deficiencies that require attention. The use of a technological tool to schedule the entry and exit of trucks is proposed, as well as analysis using digital simulations that allow for the prediction of scenarios. and the establishment of efficient schedules. The objective is to optimize vehicle flow, minimize waiting times, and avoid congestion. The methodology applied is descriptive with a quantitative approach, including field studies that provided real data on vehicle behavior. The data collected through manual counting and simulations will be used to identify critical points and propose comprehensive solutions. In turn, the results obtained were the optimization of routes for heavy transport, reducing its interaction with local traffic flow. The conclusions are to integrate digital technologies and sustainable approaches into transport planning, cities such as the one that houses the Port of Bolívar are moving towards more efficient, safer, and adaptable urban models. Strategic decisions, now based on solid evidence, will allow future investments, such as the installation of automated systems or railway infrastructure, to be more accurate, profitable, and have less environmental impact.