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7 de jul. de 2020 · Traffic prediction is a vital part of intelligent transportation systems. The ability of traffic risk prediction is of great significance to prevent traffic accidents and reduce the damages in a proactive way. Because of the complexity, uncertainty and dynamics of spatiotemporal dependence of traffic flow, accurate traffic state prediction becomes a challenging issue. Most neural networks are ...
23 de ene. de 2021 · Intelligent transportation (e.g., intelligent traffic light) makes our travel more convenient and efficient. With the development of mobile Internet and position technologies, it is reasonable to collect spatio-temporal data and then leverage these data to achieve the goal of intelligent transportation, and here, traffic prediction plays an important role. In this paper, we provide a ...
9 de oct. de 2020 · An improved hybrid predicting model including two steps: decomposition and prediction to predict highway traffic flow is proposed including the improved weighted permutation entropy (IWPE) to obtain new reconstructed components. For intelligent transportation systems (ITSs), reliable and accurate real-time traffic flow prediction is an important step and a necessary prerequisite for ...
3 de jun. de 2020 · Several prediction models of traffic flow were developed recently which can be employed in abnormal ... Highway traffic accident prediction using VDS big data analysis. J Supercomput 72(7):2815–2831. Article Google Scholar Sun H, Liu HX, Xiao H, He RR, Ran B (2003) Use of local linear regression model for short-term traffic ...
31 de ago. de 2022 · In this section, we introduce a method for predicting traffic flow based on data acquired from highway gantry using a long short-term memory network (LSTM), the architecture of the short-term traffic flow prediction algorithm based on the LSTM model is shown in Figure 1, which includes the following steps: Step 1: The highway gantry separately collects the traffic flow data sets on adjacent ...
20 de ene. de 2016 · Lv Y, Tang S, Zhao H (2009) Real-time highway traffic accident prediction based on the \(k\)-nearest neighbor method. In: International conference on measuring technology and mechatronics automation (ICMTMA), vol 3, pp 547–550. Yu R, Liu X (2010) Study on traffic accidents prediction model based on RBF neural network.
Abstract: Freeway traffic flow prediction is of great significance to freeway traffic management, route planning, toll strategy development and public safety. Existing traffic flow prediction methods mainly use deep learning models, which mainly have the following two problems: on the one hand, the special characteristics of the highway network structure make the common urban network traffic ...
