Documento de conferencia

Proactive Intelligent System for Optimizing Traffic Signaling

Conference Proceeding cp
Proceedings - 2016 IEEE 14th International Conference on Dependable, Autonomic and Secure Computing, DASC 2016, 2016 IEEE 14th International Conference on Pervasive Intelligence and Computing, PICom 2016, 2016 IEEE 2nd International Conference on Big Data Intelligence and Computing, DataCom 2016 and 2016 IEEE Cyber Science and Technology Congress, CyberSciTech 2016, DASC-PICom-DataCom-CyberSciTech 2016
  • Fecha: 11 octubre 2016
  • Páginas: 544-551
  • ISBN: 9781509040650
  • Tipo de fuente: Ponencia
  • DOI: 10.1109/DASC-PICom-DataCom-CyberSciTec.2016.104
  • Tipo de documento: Documento de conferencia
  • Editorial: Institute of Electrical and Electronics Engineers Inc.
© 2016 IEEE. Adaptive control systems for traffic signaling has been one of the most productive and studied research areas in the field of Intelligent Transportation Systems (ITS), as an effective solution to mitigate congestion and avoid its negative effects, and at the same time improving traffic flow and mobility. Nevertheless, the best methods in terms of traffic performance usually present a high computational cost and an unaffordable real implementation and/or go-to-market strategy. With the advent of the Internet of Things, the possibilities of developing new techniques, systems, applications, and services for ITS able to take advantage of the IoT capabilities (e.g., low-cost) will be huge. In this paper, we contribute to the convergence of these two paradigms by introducing PROA, a PROActive intelligent system for optimizing traffic signaling. Based on two modules, i) a new image processing algorithm acting as a traffic-monitoring tool that provides statistical data on vehicle traffic and ii) a novel adaptive traffic signaling algorithm to adjust traffic lights in accordance with the current network conditions, PROA is able to improve key metrics on traffic performance with a low computational complexity.

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