- author = "Jonathan Geovanny {Velasquez Mora} and Carlos Patricio {Arroyo Vilela}",
- title = "Modern Control Systems for industrial processes: State of the art for cases of traffic congestion, through resolution of genetic and control algorithms",
- title_es = "Sistemas de Control Moderno para procesos industriales: Estado del arte para casos de congestion vehicular, mediante resolucion d algoritmos geneticos y de control",
- journal = "La realidad tecnologica en tiempos de inteligencia artificial en Institutos Tecnologicos de Ecuador",
- year = "2024",
- volume = "3",
- number = "5",
- pages = "1296--1321",
- keywords = "genetic algorithms, genetic programming, Road Traffic, neural networks, ANN, Control, trafico, redes neuronales, controlador",
- ISSN = "2953-6421",
-
URL = "
https://www.reincisol.com/ojs/index.php/reincisol/article/view/151/276",
-
DOI = "
doi:10.59282/reincisol.V3(5)1296-1321",
- size = "26 pages",
-
abstract = "The steady increase of vehicles on the roads has
recently made road congestion a crucial challenge. To
cope with current traffic conditions and meet the
growing demand for transportation, effective solutions
are needed in urban transportation systems. However,
introducing changes in urban infrastructures often
involves significant constraints in time and
feasibility. Therefore, optimizing traffic signal
timing (TST) emerges as one of the fastest and most
cost-effective methods to reduce congestion at
intersections and improve traffic flow in urban
networks. Researchers have been exploring various
approaches, along with technological advances, to
improve TST. This article aims to review recent
literature from January 2015 to January 2020, focusing
on computational intelligence (CI)-based simulation
approaches and CI-based strategies for optimizing TST
and traffic signal control (TSC) systems. Through this
analysis, we seek to provide insight into existing
research, identify gaps, and suggest possible
directions for future research in this field.
Given the complex dynamics of traffic flows, simulation tools play a crucial role in the analysis of their behavior. Currently, microsimulation tools are widely used in TST-related research. Therefore, this article provides a critical review of some of the most widely used microsimulation packages to illuminate their effectiveness and applicability. Our review highlights that approximately 77% of the articles reviewed employ some form of microsimulation tool. Therefore, it is clearly beneficial to conduct a review, categorization, and comparison of the predominant microsimulation tools to guide future research. In conclusion, we provide insight into the future trajectory of research in these areas, paving the way for further advances and innovations.",
-
notes = "In Spanish
Corporacion Electrica del Ecuador",
