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19 de nov. de 2022 · The system consists of four parts: (1) An analysis of actual traffic conditions, that is, calculation of traffic volume, density and speed; (2) Establishment of traffic flow state...
Abstract. Traffic flow prediction is an essential part of the intelligent transport system. This is the accurate estimation of traffic flow in a given region at a particular interval of time in the future. The study of traffic forecasting is useful in mitigating congestion and make safer and cost-efficient travel.
29 de abr. de 2020 · Data-driven analysis and forecasting of highway traffic dynamics. A. M. Avila & I. Mezić. Nature Communications 11, Article number: 2090 ( 2020 ) Cite this article. 14k Accesses. 64...
24 de nov. de 2021 · Analysis and comparison of traffic flow models: a new hybrid traffic flow model vs benchmark models. Facundo Storani, Roberta Di Pace, Francesca Bruno & Chiara Fiori. European Transport Research Review 13, Article number: 58 ( 2021 ) Cite this article. 7654 Accesses. 19 Citations. Metrics. Abstract. Background.
25 de dic. de 2023 · Computing and analyzing traffic parameters on different time scales is crucial for enhancing the accuracy of highway control. Meanwhile, accurate prediction of traffic parameters plays a crucial role in fostering sustainable transportation by enabling efficient traffic management, which leads to reduced congestion and lower emissions.
9 de sept. de 2014 · This situation inspires us to rethink the traffic flow prediction problem based on deep architecture models with big traffic data. In this paper, a novel deep-learning-based traffic flow prediction method is proposed, which considers the spatial and temporal correlations inherently.
model-free, data-driven approach for analyzing and forecasting traffic dynamics. By obtaining a decomposition of data sets collected by the Federal Highway Administration and the
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