The invention provides a traffic flow data completion method, a model training method, devices and equipment, and relates to the field of artificial intelligence and intelligent traffic. According to the specific implementation scheme, the method comprises the steps of obtaining road network data and vehicle driving data in a traffic area, and historical flow data monitored at a non-target intersection of the traffic area; obtaining historical flow complementation data of a non-target intersection and initial flow complementation data of a target intersection based on track mapping characteristics between the road network data and the vehicle driving data; performing fusion processing on the historical traffic data, the historical traffic completion data and the initial traffic completion data to obtain corrected traffic data of the non-target intersection; and obtaining target traffic complementation data of the target intersection based on the trajectory mapping features, the corrected traffic data and the spatial correlation features between the initial traffic complementation data. The problem of real-time traffic flow loss caused by high equipment cost is solved, and more complete data support is provided for optimization of a traffic signal control system.
本公开提供了交通流量数据的补全方法、模型训练方法、装置和设备,涉及人工智能和智能交通领域。具体实现方案为:获取交通区域内的路网数据和车辆行驶数据,以及在交通区域的非目标路口监测到的历史流量数据;基于路网数据和车辆行驶数据之间的轨迹映射特征,获得非目标路口的历史流量补全数据和目标路口的初步流量补全数据;对历史流量数据、历史流量补全数据和初步流量补全数据进行融合处理,获得非目标路口的修正流量数据;基于轨迹映射特征、修正流量数据和初步流量补全数据之间的空间关联特征,获得目标路口的目标流量补全数据。本公开解决了因设备成本高昂导致的实时交通流量缺失问题,为交通信控系统的优化提供更完整的数据支持。
Traffic flow data completion method, model training method, device and equipment
交通流量数据的补全方法、模型训练方法、装置和设备
2024-04-19
Patent
Electronic Resource
Chinese
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