The invention relates to a traffic scheduling method, device and equipment, a medium and a program product. The method comprises the steps that real-time traffic data of a target area is acquired, the real-time traffic data can be further processed through a pre-trained deep learning model, a traffic prediction result can represent the future traffic condition of the target area, and a traffic scheduling strategy is formulated and executed based on the obtained traffic prediction result. The deep learning model is trained by using the traffic data in advance, so that the deep learning model can automatically learn traffic modes and rules, a high-precision and real-time traffic prediction result is provided according to the real-time traffic data, the traffic scheduling difficulty is reduced, effective scheduling can be performed by means of the traffic prediction result, traffic congestion is relieved, and the traffic scheduling efficiency is improved. The traffic condition is improved.
本发明涉及一种交通调度方法、装置、设备、介质及程序产品。该方法包括:获取目标区域的实时交通数据,可以进一步通过预训练的深度学习模型对实时交通数据进行处理,该交通预测结果可以表征所述目标区域未来的交通状况,基于得到的交通预测结果制定并执行交通调度策略。通过预先使用交通数据训练深度学习模型,可以使深度学习模型自动学习交通模式和规律,并根据实时交通数据提供高精度和实时性的交通预测结果,降低交通调度的难度,从而可以借助交通预测结果进行有效调度,缓解交通拥堵,改善交通状况。
Traffic scheduling method, device, equipment, medium and program product
交通调度方法、装置、设备、介质及程序产品
2025-04-25
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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