Ponente
Descripción
Urban traffic congestion remains a critical challenge in modern cities due to the increasing demand for transportation and the limited capacity of road infrastructure. This issue not only leads to longer travel times but also contributes to higher fuel consumption and increased emissions of pollutants. Mexico is no exception; major cities, including Puebla, face severe problems related to traffic congestion and road safety, highlighting the urgent need for efficient urban mobility systems. This research addresses these challenges through the estimation of parameters in microscopic car-following traffic models. Various traffic modeling approaches exist to analyze vehicular dynamics and support infrastructure planning and decision-making. Broadly, traffic flow models are categorized into macroscopic and microscopic models. Macroscopic models draw analogies from fluid dynamics to describe traffic flow, while microscopic models focus on the individual behavior of each vehicle, capturing interactions between drivers and nearby vehicles. A third category, mesoscopic models, offers a trade-off between the detail of microscopic approaches and the simplicity of macroscopic models. This study specifically focuses on microscopic car-following models as a tool for understanding and improving traffic behavior at a granular level.
