Browsing by Author "Pezoa, Adrián"

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    Inefficient Mobility in the Cities: AI-Powered Smart Traffic Lights
    (Inglés II. Universidad Tecnológica Nacional. Facultad Regional Paraná, 2025-12) Avilé, Marcos; Laclé-Pereira, Gabriela; Pezoa, Adrián
    Abstract— Currently, in modern cities, one of the principal challenges is the efficient management of urban traffic. Factors such as the population growth, the increase in the vehicle fleet, and the lack of adaptation of the traffic light system to real conditions in real time generate vehicular congestion and environmental problems, and these situations cause inefficient mobility in cities. This problem can be solved or diminished in their effects by means of the use of a network of intelligent traffic lights based on data taken in real time through artificial intelligence (AI). The purpose of this paper is to analyse the feasibility of efficient management of urban traffic networks in real time. To fulfil this purpose, this paper is organized as follows: First, the problem of inefficient mobility in cities is described using data gathered from a variety of a sources, for example, reports from cities like Los Angeles, Buenos Aires, New York. Second, based on this analysis, a technological solution for real time traffic management is proposed by means of AI-powered smart traffic lights. Third, advantages, and limitations of the solution are assessed. This paper aims to contribute to the analysis of the effectiveness of AI-powered, data-driven strategies for urban traffic management, emphasizing their potential to advance sustainable urban development.