- -

Arquitectura distribuida modular para el control inteligente del tráfico

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Arquitectura distribuida modular para el control inteligente del tráfico

Mostrar el registro completo del ítem

Uribe-Chavert, P.; Posadas-Yagüe, J.; Balbastre, P.; Poza-Luján, J. (2022). Arquitectura distribuida modular para el control inteligente del tráfico. Revista Iberoamericana de Automática e Informática industrial. 20(1):56-67. https://doi.org/10.4995/riai.2022.17068

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/191367

Ficheros en el ítem

Thumbnail
Nombre: Uribe-ChavertPosa ...
Tamaño: 1.374Mb
Formato: PDF
Descripción: Versión editorial
Abrir/Preview

Metadatos del ítem

Título: Arquitectura distribuida modular para el control inteligente del tráfico
Otro titulo: Modular distributed architecture for intelligent traffc control
Autor: Uribe-Chavert, Pedro Posadas-Yagüe, Juan-Luis Balbastre, Patricia Poza-Luján, José-Luis
Entidad UPV: Universitat Politècnica de València. Instituto Universitario de Automática e Informática Industrial - Institut Universitari d'Automàtica i Informàtica Industrial
Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica
Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials
Fecha difusión:
Resumen:
[EN] The management of people and vehicles mobility is an aspect of continuous study due to its contribution to pollution. Traffic light control determines the queues that can form at crossroads. Usually, this control is ...[+]


[ES] La gestión de la movilidad de personas y vehículos es un aspecto de continuo estudio debido a la relevancia que tiene en la contribución a la polución. El control de los semáforos determina las colas que en los cruces ...[+]
Palabras clave: Distributed systems , Intelligent control , Traffic control , Urban systems , Sistemas distribuidos , Control inteligente , Control de tráfico , Sistemas urbanos
Derechos de uso: Reconocimiento - No comercial - Compartir igual (by-nc-sa)
Fuente:
Revista Iberoamericana de Automática e Informática industrial. (issn: 1697-7912 ) (eissn: 1697-7920 )
DOI: 10.4995/riai.2022.17068
Editorial:
Universitat Politècnica de València
Versión del editor: https://doi.org/10.4995/riai.2022.17068
Código del Proyecto:
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-86520-C3-1-R/ES/SISTEMAS INFORMATICOS PREDECIBLES Y CONFIABLES PARA LA INDUSTRIA 4.0/
Agradecimientos:
Ministerio de Ciencia e Innovación de España Proyecto MICINN: CICYT PRECON-I4: Sistemas informáticos predecibles y confiables para la Industria 4.0 TIN2017-86520-C3-1-R
Tipo: Artículo

References

Al-qutwani, M.,Wang, X., 2019. Smart traffic lights over vehicular named data networking. Information 10 (3), 83. https://doi.org/10.3390/info10030083

Banister, D., 2011. Cities, mobility and climate change. Journal of Transport Geography 19 (6), 1538-1546. https://doi.org/10.1016/j.jtrangeo.2011.03.009

Beaver, L. E., Chalaki, B., Mahbub, A. I., Zhao, L., Zayas, R., Malikopoulos, A. A., 2020. Demonstration of a time-efficient mobility system using a scaled smart city. Vehicle System Dynamics 58 (5), 787-804. https://doi.org/10.1080/00423114.2020.1730412 [+]
Al-qutwani, M.,Wang, X., 2019. Smart traffic lights over vehicular named data networking. Information 10 (3), 83. https://doi.org/10.3390/info10030083

Banister, D., 2011. Cities, mobility and climate change. Journal of Transport Geography 19 (6), 1538-1546. https://doi.org/10.1016/j.jtrangeo.2011.03.009

Beaver, L. E., Chalaki, B., Mahbub, A. I., Zhao, L., Zayas, R., Malikopoulos, A. A., 2020. Demonstration of a time-efficient mobility system using a scaled smart city. Vehicle System Dynamics 58 (5), 787-804. https://doi.org/10.1080/00423114.2020.1730412

Burguillo-Rial, J. C., Rodriguez-Hernandez, P. S., Montenegro, E. C., Castineira, F. G., 2012. History-based self-organizing traffic lights. Computing and Informatics 28 (2), 157-168.

Chen, L.-W., Chang, C.-C., 2016. Cooperative traffic control with green wave coordination for multiple intersections based on the internet of vehicles. IEEE Transactions on Systems, Man, and Cybernetics: Systems 47 (7),1321-1335. https://doi.org/10.1109/TSMC.2016.2586500

De Souza, A. M., Brennand, C. A., Yokoyama, R. S., Donato, E. A., Madeira, E. R., Villas, L. A., 2017. Traffic management systems: A classification, review, challenges, and future perspectives. International Journal of Distributed Sensor Networks 13 (4), 1550147716683612. https://doi.org/10.1177/1550147716683612

Gao, K., Huang, S., Han, F., Li, S., Wu, W., Du, R., 2020. An integrated algorithm for intersection queue length estimation based on iot in a mixed traffic scenario. Applied Sciences 10 (6), 2078. https://doi.org/10.3390/app10062078

Griggs, D., Stafford-Smith, M., Gaffney, O., Rockström, J., Öhman, M. C., Shyamsundar, P., Steffen, W., Glaser, G., Kanie, N., Noble, I., 2013. Policy: Sustainable development goals for people and planet. Nature 495 (7441), 305. https://doi.org/10.1038/495305a

Hartanti, D., Aziza, R. N., Siswipraptini, P. C., 2019. Optimization of smart traffic lights to prevent traffic congestion using fuzzy logic. TELKOMNIKA. Telecommunication Computing Electronics and Control 17 (1), 320-327. https://doi.org/10.12928/telkomnika.v17i1.10129

Hernandez Bel, A., 2020. Dispositivo modular configurable para la deteccion de vehıculos, y viandantes, y con soporte a la iluminacion de la va e informacion de trafico. Tech. rep., Universitat Polit'ecnica de Valencia.

Jang, H.-C., Lin, T.-K., 2018. Traffic-aware traffic signal control framework based on sdn and cloud-fog computing. In: 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall). IEEE, pp. 1-5. https://doi.org/10.1109/VTCFall.2018.8690602

Lämmer, S., Helbing, D., 2008. Self-control of traffic lights and vehicle flows in urban road networks. Journal of Statistical Mechanics: Theory and Experiment 2008 (04), P04019. https://doi.org/10.1088/1742-5468/2008/04/P04019

Liang, X., Du, X., Wang, G., Han, Z., 2018. Deep reinforcement learning for traffic light control in vehicular networks. arXiv preprint arXiv:1803.11115.

Liu, H. X.,Wu, X., Ma,W., Hu, H., 2009. Real-time queue length estimation for congested signalized intersections. Transportation research part C: emerging technologies 17 (4), 412-427. https://doi.org/10.1016/j.trc.2009.02.003

Mahoor, M., Salmasi, F. R., Najafabadi, T. A., 2017. A hierarchical smart street lighting system with brute-force energy optimization. IEEE Sensors Journal 17 (9), 2871-2879. https://doi.org/10.1109/JSEN.2017.2684240

Navarro, J., Vida˜na-Vila, E., Alsina-Pagés, R. M., Hervas, M., 2018. Real-time distributed architecture for remote acoustic elderly monitoring in residential scale ambient assisted living scenarios. Sensors 18 (8), 2492. https://doi.org/10.3390/s18082492

Pell, A., Meingast, A., Schauer, O., 2017. Trends in real-time traffic simulation. Transportation research procedia 25, 1477-1484. https://doi.org/10.1016/j.trpro.2017.05.175

Płaczek, B., 2014. A self-organizing system for urban traffic control based on predictive interval microscopic model. Engineering applications of artificial intelligence 34, 75-84. https://doi.org/10.1016/j.engappai.2014.05.004

Poza-Lujan, J.-L., Posadas-Yagüe, J.-L., Simó-Ten, J.-E., Blanes, F., 2020. Distributed architecture to integrate sensor information: Object recognition forsmart cities. Sensors 20 (1), 112. https://doi.org/10.3390/s20010112

Poza-Lujan, J.-L., Uribe-Chavert, P., Sáenz-Peñafiel, J.-J., Posadas-Yagüe, J.-L., 2021. Distributing and processing data from the edge. a case study with ultrasound sensor modules. In: International Symposium on Distributed Computing and Artificial Intelligence. Springer, pp. 190-199. https://doi.org/10.1007/978-3-030-86261-9_19

Poza-Lujan, J.-L., Uribe-Chavert, P., Sáenz-Peñafiel, J.-J., Posadas-Yagüe, J.-L., 2022. Processing at the edge: A case study with an ultrasound sensor-based embedded smart device. Electronics 11 (4), 550. https://doi.org/10.3390/electronics11040550

Sachs, J. D., 2012. From millennium development goals to sustainable development goals. The Lancet 379 (9832), 2206-2211. https://doi.org/10.1016/S0140-6736(12)60685-0

Simarro Fernandez, R., Simo Ten, J. E., Navarro Herrero, J. L., Poza-Lujan, J.-L., Posadas-Yagüe, J.-L., 2016. Nucleo de control: Controladores modulares en entornos distribuidos. Revista Iberoamericana de Automatica e Informatica Industrial (RIAI) 13 (2), 196-206. https://doi.org/10.1016/j.riai.2015.11.005

Tiaprasert, K., Zhang, Y., Wang, X. B., Zeng, X., 2015. Queue length estimation using connected vehicle technology for adaptive signal control. IEEE Transactions on Intelligent Transportation Systems 16 (4), 2129-2140. https://doi.org/10.1109/TITS.2015.2401007

Tubaishat, M., Shang, Y., Shi, H., 2007. Adaptive traffic light control with wireless sensor networks. In: 2007 4th IEEE Consumer Communications and Networking Conference. IEEE, pp. 187-191. https://doi.org/10.1109/CCNC.2007.44

Uribe Chavert, P., 2020. Sistema de control de trafico automatico basado en dispositivos modulares heterog"€eneos. Tech. rep., Universitat Politecnica de Valencia.

Wen, W., 2008. A dynamic and automatic traffic light control expert system for solving the road congestion problem. Expert Systems with Applications 34 (4), 2370-2381. https://doi.org/10.1016/j.eswa.2007.03.007

[-]

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem