The invention discloses a highway traffic anomaly detection method based on a multi-dimensional matrix portrait. The method comprises the steps of data acquisition and preprocessing: acquiring data through vehicle-mounted navigation software; preprocessing the data to form a space-time grid data structure; data preparation: selecting a road section with more traffic anomalies from the data of different road sections as a data sample; constructing a traffic anomaly detection algorithm based on a multi-dimensional matrix portrait to carry out anomaly detection on the data sample, and judging whether an anomaly occurs or not; and the optimal parameters of the traffic anomaly detection algorithm are determined through cross validation. According to the method, the anomalies in the data set are detected by comparing the distances between different subsequences, the sensitivity of the algorithm to data changes is increased by introducing a local dynamic threshold value and continuous detection, and the anomalies can be positioned more accurately.
本发明公开了一种基于多维矩阵画像的高速公路交通异常检测方法,包括数据获取和预处理:通过车载导航软件获取数据;对数据进行预处理形成时空网格的数据结构;数据准备:从不同路段的数据中选择发生交通异常较多的路段作为数据样本;构建基于多维矩阵画像的交通异常检测算法对数据样本进行异常检测,判断是否发生异常;并通过交叉验证确定交通异常检测算法的最优参数。本发明通过比较不同子序列之间的距离来检测数据集中的异常,引入了局域动态阈值和持续性检测增加了算法对数据变化的灵敏度,能够实现对异常更加精准的定位。
Expressway traffic anomaly detection method based on multi-dimensional matrix portrait
一种基于多维矩阵画像的高速公路交通异常检测方法
2024-02-27
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
Wiley | 2024
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