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Smart city article details

Title	Mobility Trace Analysis For Intelligent Vehicular Networks
ID_Doc	37374
Authors	Celes C.; Boukerche A.; Loureiro A.A.F.
Year	2022
Published	ACM Computing Surveys, 54, 3
DOI	http://dx.doi.org/10.1145/3446679
Abstract	Intelligent vehicular networks emerge as a promising technology to provide efficient data communication in transportation systems and smart cities. At the same time, the popularization of devices with attached sensors has allowed the obtaining of a large volume of data with spatiotemporal information from different entities. In this sense, we are faced with a large volume of vehicular mobility traces being recorded. Those traces provide unprecedented opportunities to understand the dynamics of vehicular mobility and provide data-driven solutions. In this article, we give an overview of the main publicly available vehicular mobility traces; then, we present the main issues for preprocessing these traces. Also, we present the methods used to characterize and model mobility data. Finally, we review existing proposals that apply the hidden knowledge extracted from the mobility trace for vehicular networks. This article provides a survey on studies that use vehicular mobility traces and provides a guideline for the proposition of data-driven solutions in the domain of vehicular networks. Moreover, we discuss open research problems and give some directions to undertake them. © 2021 ACM.
Author Keywords	data analysis; data mining; mobility; routing; survey; topology; vanet; Vehicular networks

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