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Título : Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata
Autor: Zapotecatl, Jorge L.
Otros autores : Gershenson, Carlos
Rosenblueth Laguette, David Arturo
En: Complexity (1076-2787), Article ID 7691370, 15 pages, (2017)
Número completo : https://www.hindawi.com/journals/complexity/contents/year/2017/
Editorial : Hindawi
Abstract : Self-organizing traffic lights have shown considerable improvements compared to traditional methods in computer simulations. Self-organizing methods, however, use sophisticated sensors, increasing their cost and limiting their deployment. We propose a novel approach using simple sensors to achieve self-organizing traffic light coordination. The proposed approach involves placing a computer and a presence sensor at the beginning of each block; each such sensor detects a single vehicle. Each computer builds a virtual environment simulating vehicle movement to predict arrivals and departures at the downstream intersection. At each intersection, a computer receives information across a data network from the computers of the neighboring blocks and runs a self-organizing method to control traffic lights. Our simulations showed a superior performance for our approach compared with a traditional method (a green wave) and a similar performance (close to optimal) compared with a self-organizing method using sophisticated sensors but at a lower cost. Moreover, the developed sensing approach exhibited greater robustness against sensor failures.
Area del conocimiento : Ciencias Físico Matemáticas y Ciencias de la Tierra
Palabras clave en inglés : Cellular Automata
Computer simulations
Self-organizing methods
Sensors
Fecha de publicación : 30-may-2017
DOI : http://dx.doi.org/10.1155/2017/7691370
URI : http://www.ru.iimas.unam.mx/handle/IIMAS_UNAM/ART29
Idioma: Inglés
Lugar: Estados Unidos
Citación : Zapotecatl, J. L., Rosenblueth, D. A. & Gershenson, C. (2017). Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata. Complexity. Article ID 7691370, 15 pages. doi: 10.1155/2017/7691370
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