Abstract
Nowadays, one of the main challenges faced in large metropolitan areas is traffic congestion. To address this problem, an adequate traffic control could produce many benefits, including reduced pollutant emissions and reduced travel times. If it were possible to characterize the state of traffic by predicting traffic conditions, measures could be taken to preventively mitigate the effects of congestion and related problems. This paper performs an experimental study of the traffic distribution in the city of Valencia, characterizing the different streets of the city in terms of vehicle load with respect to the travel time during rush hour traffic conditions. Experimental results based on realistic vehicular traffic traces show that most of the street segments under analysis present a good fit under quadratic regression, although a large number of street segments fall under other categories mainly due to lack of traffic. Based on this study, a clustering analysis study associated to the different streets shows how these streets can be classified into four independent categories, evidencing an uneven traffic distribution throughout the city.
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Acknowledgments
This work was partially supported by Valencia’s Traffic Management Department, by the “Ministerio de Economía y Competitividad, Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad, Proyectos I+D+I 2014”, Spain, under Grant TEC2014-52690-R, and the “Programa de Becas SENESCYT” de la República del Ecuador.
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Zambrano-Martinez, J.L., Calafate, C.T., Soler, D., Cano, JC., Manzoni, P. (2017). Analysis and Classification of the Vehicular Traffic Distribution in an Urban Area. In: Puliafito, A., Bruneo, D., Distefano, S., Longo, F. (eds) Ad-hoc, Mobile, and Wireless Networks. ADHOC-NOW 2017. Lecture Notes in Computer Science(), vol 10517. Springer, Cham. https://doi.org/10.1007/978-3-319-67910-5_10
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DOI: https://doi.org/10.1007/978-3-319-67910-5_10
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