The invention relates to the technical field of highway traffic analysis, in particular to a highway section traffic state judgment method, which comprises the following steps of: firstly, acquiring historical data of a section portal frame and a toll station, and eliminating abnormal data such as irrelevant fields, incomplete access information, overlong section travel time and the like; calculating traffic flow parameters such as interval traffic flow, average travel speed and density; carrying out clustering analysis on the traffic flow parameters by adopting a fuzzy clustering algorithm based on mahalanobis distance, and dividing traffic flow states; and finally, acquiring real-time traffic flow parameter data, and judging the traffic state according to the distance from the state class center. According to the method, the Mahalanobis distance is used for replacing the Euclidean distance for fuzzy clustering analysis, the problem that the Euclidean distance is low in precision when the attribute related data set is calculated is well solved, the traffic state division accuracy is further improved, and the method can be suitable for judging the traffic state on the highway section.
本发明涉及公路交通分析技术领域,具体涉及一种高速公路路段交通状态判别方法,首先获取区段龙门架和收费站历史数据,剔除无关字段、出入信息不全及区段行程时间过长等异常数据;计算求得区间车流量、平均行程速度和密度等交通流参数;采用基于马氏距离的模糊聚类算法对交通流参数进行聚类分析,划分交通流状态;最后获取实时交通流参数数据,并根据距离状态类中心的距离对交通状态进行判断。本发明利用马氏距离代替欧式距离进行模糊聚类分析,很好地解决欧式距离在计算属性相关数据集时精度较低的问题,进一步提高交通状态划分准确性,可适用于对高速公路路段上交通状态的判断。
Expressway section traffic state discrimination method
一种高速公路路段交通状态判别方法
2024-03-15
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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