The invention discloses a distributed traffic flow prediction method based on fog computing. The method comprises the following steps: S1, carrying out regional-level modeling on an urban traffic network; s2, carrying out preprocessing according to the traffic flow data, collected by the fog server, of the local road; s3, a Conv-LSTM model is constructed according to the collected data, and parameter tuning is carried out; and S4, outputting a prediction result according to the model in the step S3 and the input traffic flow data. A centralized system is difficult to expand, faults can provide real-time feedback for the system, and in a distributed scheme provided by the invention, each road section can predict own short-term congestion according to an adjacent local current measurement value.
本发明公开了一种基于雾计算的分布式的交通流预测方法,所述方法包括:S1:对城市交通网络进行区域级别的建模;S2:根据雾服务器所收集到的局部道路的交通流数据进行预处理;S3:根据所收集到的数据构建Conv‑LSTM模型,进行参数调优;S4:根据S3步骤的模型及输入的交通流数据输出预测结果。集中式系统是难以扩展的,故障会向系统提供实时反馈,而在本发明提出的分布式方案中,每个路段可根据邻近本地当前测量值预测自己的短期拥塞。
Distributed urban short-term traffic flow prediction method based on fog computing
一种基于雾计算的分布式城市短时交通流预测方法
2023-09-05
Patent
Electronic Resource
Chinese
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