The invention discloses a road traffic condition prediction method, device and equipment based on a smart city. The method comprises the following steps: acquiring position information of an easily blocked road section; obtaining at least one inevitable road section reaching the easily blocked road section; training through a neural network model to obtain a first relation model between the traffic flow of each necessary road section at the same time and the traffic jam of the easy-to-block road section; collecting the traffic flow of each inevitable road section at a specific time; and inputting the traffic flow into the first relation model so as to predict the traffic jam degree of the easily-blocked road section after a preset time. According to the invention, the relation model of the plurality of necessary road sections and the easy-to-block road section is constructed, and the traffic jam degree of the easy-to-block road section at the future moment is calculated through the traffic flow information of the plurality of necessary road sections at the current moment, so that the prediction of whether the traffic jam occurs in a certain easy-to-block road section in the future is realized. And thus, an effective reference is provided for travel of people.
本发明公开了一种基于智慧城市的道路交通状况预测方法、装置及设备,方法包括:获取易阻塞路段的位置信息;获取到达所述易阻塞路段的至少一个必经路段;通过神经网络模型训练得到各个必经路段在同一时间的车流量与所述易阻塞路段发生塞车之间的第一关系模型;采集在特定时间各个必经路段的车流量;将所述车流量输入所述第一关系模型,以预测所述易阻塞路段在经过预定时间后发生塞车的塞车程度。本发明通过构建多个必经路段与所述易阻塞路段的关系模型,再通过多个必经路段在当前时刻的车流量信息对未来时刻易阻塞路段的塞车程度进行计算,从而实现了对某个易阻塞路段在未来是否发生塞车的预测,进而为人们的出行提供了有效的参考。
Road traffic condition prediction method, device and equipment based on smart city
基于智慧城市的道路交通状况预测方法、装置、设备
2021-11-05
Patent
Electronic Resource
Chinese
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