The invention relates to the field of traffic information analysis, in particular to a festival and holiday long-term traffic situation prediction method and device based on a time sequence model. According to the method, the influence of occurrence of major events on road network holiday traffic flow is considered, a holiday long-term traffic situation prediction model based on an SARIMAX (seasonal autoregressive moving smoothing with exogenous variables) model is established, and an epidemic situation influence factor and an exponential decay function factor considering a trend term weight are introduced; and the influence of weather (precipitation, visibility and weather conditions) data is considered, so that the accuracy and reliability of traffic flow prediction are improved. The prediction result is divided into a road network flow long-term prediction result and a road section flow long-term prediction result, so that more convenient and more effective decision support is provided for road managers.
本发明涉及交通信息分析领域,特别是一种基于时间序列模型的节假日长期交通态势预测方法及设备。本发明考虑重大事件的发生对路网节假日交通流量的影响,建立了一种基于SARIMAX(具有外生变量的季节性自回归移动平滑)模型的节假日长期交通态势预测模型,引入了疫情影响因子和考虑趋势项权重的指数衰减函数因子,并考虑天气(降水量、能见度、天气状况)数据的影响,以提高交通流预测的准确性和可靠性。预测结果分为路网流量长期预测结果和路段流量长期预测结果,以便为道路管理者提供更便利更有效的决策支持。
Festival and holiday long-term traffic situation prediction method and device based on time sequence model
基于时间序列模型的节假日长期交通态势预测方法及设备
2024-06-07
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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