The invention, which belongs to the field of intelligent traffic systems, provides a traffic state estimation method based on kmeans clustering and deep sequence learning, thereby solving the problemthat the traffic state of a whole expressway cannot be estimated under the condition that traffic flow data of part of road sections in the urban expressway cannot be acquired in real time. The methodis characterized by comprising the following steps: (1), dividing an expressway network; (2), carrying out modeling and data acquisition of an expressway; (3), preprocessing and normalizing the data;(4), calculating the Euclidean distance between the traffic flow data through a kmeans clustering algorithm, and determining the traffic state grade of each data point; and (5), designing a deep sequence learning Seq2Seq model, and carrying out traffic state identification on the whole road network through model iterative learning. The method gives full consideration to the relation of traffic flows between road segments and gives play to the advantages of a machine learning algorithm in the traffic field; the traffic state of the whole road network can be obtained in time; and reliable traffic information can be provided for a driving main body.

    本发明提供了一种基于kmeans聚类与深度序列学习的交通状态估计方法,属于智能交通系统领域,主要解决在城市快速路中部分路段的交通流数据无法实时获取的情况下,实现对整个快速路的交通状态进行估计的问题。其特征在于,所述方法包括步骤如下:(1)快速路网划分;(2)快速路的建模与数据采集;(3)数据预处理与归一化;(4)通过kmeans聚类算法计算交通流数据间的欧氏距离,确定各数据点的交通状态等级;(5)深度序列学习Seq2Seq模型的设计,通过模型迭代学习对整个路网进行交通状态识别。本发明充分考虑了路段之间交通流的关系,发挥机器学习算法在交通领域的优势,及时得到整个路网的交通状态,可以为驾驶主体提供可靠的交通信息。


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    Title :

    Traffic state estimation method based on clustering and deep sequence learning


    Additional title:

    一种基于聚类与深度序列学习的交通状态估计方法


    Contributors:
    CHEN YANGZHOU (author) / MA PENGFEI (author) / SHI ZEYU (author)

    Publication date :

    2020-06-16


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06K Erkennen von Daten , RECOGNITION OF DATA / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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