Transportation of people and goods has a huge impact on the economy of countries. The exponential grows of vehicles in the cities brings traffic congestion consequences like pollution, high combustible consumption and lowers the quality of life of the citizens. The development of Intelligent Transportation Systems is a key component of Smart Cities; Artificial Intelligence (AI) techniques used to build Intelligent Traffic Light Controllers (ITLC). This paper presents a survey of current technologies being use in the development of ITLC; many of them are experimental and tested in simulators, which show that implanting ITLC systems in real scenarios is difficult and expensive. The main objective of this survey is to find related work and algorithms to control traffic in real-time scenarios with AI. Artificial Vision rises as a promising technology for building reliable Intelligent Traffic Lights (ITL) as the technology evolves the error rate is decreasing, and more applications appear such as vehicle counting and classification, identifying vehicle’s moving patterns and giving priority for emergency vehicles. Furthermore, ITL implementation discussed, and the algorithms and different solutions compared.


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    Titel :

    A Survey on Intelligent Traffic Lights


    Beteiligte:
    Jacome, Luis (Autor:in) / Benavides, Leonardo (Autor:in) / Jara, Diejo (Autor:in) / Riofrio, Gonzalo (Autor:in) / Alvarado, Fabricio (Autor:in) / Pesantez, Manuel (Autor:in)


    Erscheinungsdatum :

    01.10.2018


    Format / Umfang :

    275225 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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