The invention discloses a ground road lane-level traffic flow prediction method based on a space-time attention mechanism. The method comprises the steps of preprocessing original traffic flow data; formulating a lane selection strategy; carrying out speed processing and space encoder network self-learning; and obtaining a final prediction result through tensor fusion and time decoder network self-learning. According to the invention, through a space-time attention mechanism network of a coding and decoding structure, deep features of traffic flow are captured, and the problem of long-distance dependence is efficiently solved in a parallel mode. Meanwhile, a specific ground lane selection strategy is verified through a grey correlation analysis method. A refined lane-level traffic flow prediction result can be obtained, and traffic management can be better served.
基于时空注意力机制的地面道路车道级交通流预测方法,预处理原始交通流数据;制定车道选取策略;进行速度处理及空间编码器网络自学习;通过张量融合并进行时间解码器网络自学习获取最终预测结果。本发明通过编解码结构的时空注意力机制网络,捕获交通流深层次特征,并以并行方式高效解决长距离依赖问题。同时特定的地面车道选取策略,并经灰色关联分析法验证。能取得精细化车道级交通流预测结果,更好地服务交通管理。
Ground road lane-level traffic flow prediction method based on space-time attention mechanism
基于时空注意力机制的地面道路车道级交通流预测方法
2021-06-08
Patent
Elektronische Ressource
Chinesisch
IPC: | G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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