The embodiment of the invention discloses a traffic flow statistics method, device and equipment and a storage medium. The method specifically comprises steps of obtaining training data, and traininga designed convolutional neural network according to the training data to obtain an instantaneous vehicle number estimation model; acquiring radar monitoring data, inputting the radar monitoring datainto the instantaneous vehicle number estimation model to obtain the instantaneous vehicle number, and determining a lane driving state; and judging lane driving state change information according tothe instantaneous vehicle number and the lane driving state, and counting the traffic flow according to the lane driving state change information. The method is based on radar for monitoring. The method has advantages of simple operation, low influence of light and weather, no need of destroying a road surface, low requirement on operational capability, quicker operation, low complexity of an algorithm method, easiness in realization on embedded equipment and capability of being manufactured into a portable traffic flow monitor as the data volume acquired by the radar is small and the convolutional neural network does not need to be designed very complexly.
本发明实施例公开了一种车流量统计方法、装置、设备及存储介质。该方法具体包括:获取训练数据,根据训练数据训练设计好的卷积神经网络得到瞬时车辆数估计模型;获取雷达监测数据,将雷达监测数据输入瞬时车辆数估计模型得到瞬时车辆数并确定车道行车状态;根据瞬时车辆数和车道行车状态判断车道行车状态变化信息,根据车道行车状态变化信息统计车流量。该方法基于雷达进行监测,受光线和天气影响小,也无需对路面进行破坏,由于雷达采集的数据量小其卷积神经网络无需设计的很复杂,对于运算能力要求低,运算也更快速,算法方法复杂度不高,易于在嵌入式设备上实现,可制作成便携式的车流量监测仪。
Traffic flow statistics method, device and equipment and storage medium
一种车流量统计方法、装置、设备及存储介质
2020-07-03
Patent
Elektronische Ressource
Chinesisch
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