Conceptual Model for Intelligent Urban Traffic Management Integrating MaxPressure and Industry 4.0 Technologies
DOI:
https://doi.org/10.53591/easi.V3i2.3248Keywords:
Adaptive control, Industry 4.0, MaxPressure, Traffic management, Urban mobilityAbstract
Traffic congestion is one of the main challenges facing urban mobility, especially in medium-sized cities where road capacity tends to grow more slowly than demand. To address this, this study develops a conceptual model for intelligent urban traffic management in the city of Ambato, Ecuador, integrating MaxPressure as an adaptive control core, industrial engineering tools for performance monitoring, and Industry 4.0/CPS technologies to support data capture and integration. Methodologically, the research adopts a conceptual construction approach based on the structured integration of theoretical evidence, the identification of minimal constructs, and the formulation of a traceable functional architecture. As a result, a modular architecture is proposed that articulates observation, state estimation, decision-making, execution, and feedback. The main contribution of the study consists of combining a control algorithm, an operational evaluation, and digital enablers into a single functional proposal, addressing the fragmentation with which these components are typically treated in the literature. Although the model remains conceptual in scope, it offers an explicit basis for future stages of simulation, validation, and progressive implementation.
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