The invention relates to the technical field of traffic demand estimation, in particular to a traffic demand flow estimation method, which comprises the following steps of: 1, preprocessing GPS navigation data entries, retaining date, time, equipment number, longitude, dimension and speed attributes in the entries, and screening out the rest attributes to obtain a global positioning system (GPS) navigation data entry; and then the preprocessed GPS navigation data entries are sorted according to device numbers. According to the traffic demand flow estimation method, the algorithm is designed on the basis of the existing traffic infrastructure, the sum time of operation is reduced to the maximum extent, and the kernel function algorithm adopted in the method achieves the effect of a hot spot area at the gathering position of a traditional K-means algorithm, so that the effect of reducing and optimizing data is achieved, and the traffic demand flow estimation efficiency is improved. The road traffic state, the vehicle parking time, the delay time and the like are judged by analyzing the periodic vehicle road section time data, meanwhile, errors generated by the vehicle capture rate and the license plate recognition rate of the detection equipment are considered, and the accuracy and the reliability of traffic demand flow estimation are improved.
本发明涉及交通需求估计技术领域,具体为一种交通需求流量估计方法,包括以下步骤:步骤一、对GPS导航数据词条进行预处理,保留词条中的日期、时间、设备编号、经度、维度和速度属性,将其余属性筛除,然后将预处理后的GPS导航数据词条先按照设备编号排序。该交通需求流量估计方法,在已有的交通基础设施的基础上设计算法,最大限度的减少运算的和时间,本文中采用的核函数算法,达到传统K‑means算法聚集处热点区域的效果,以得到减少和优化数据的效果,通过对周期车辆路段时间数据的分析判定道路交通状态、车辆停等时间、延误时间等,同时考虑检测设备车辆捕获率和车牌识别率产生的误差,提高了交通需求流量估计的准确度和可靠度。
Traffic demand flow estimation method
一种交通需求流量估计方法
2023-03-17
Patent
Elektronische Ressource
Chinesisch
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