本申请公开了一种基于人工智能的收费站匝道管控方法、设备及介质,采集待管控路段的视频流及传感器数据,并预处对视频流以确定关键帧图像;结合传感器数据分析关键帧图像,确定待管控路段对应的交通数据和交通影响因素值,并将交通数据和交通影响因素值输入至训练好的交通流预测模型中以输出预设时间段对应的预估交通状况;基于实时获取的车辆驾驶需求和预估交通状况,生成对应行驶车辆的推荐规划路径,并基于行驶车辆对相应推荐规划路径的确认状况优化预估交通状况;确定优化后预估交通状况对应的拥堵等级,并基于预设的匝道管控库确定拥堵等级对应的匝道管控策略,以根据匝道管控策略对收费站进行匝道管控。
The invention discloses a toll station ramp control method and device based on artificial intelligence, and a medium, and the method comprises the steps: collecting a video stream and sensor data of a to-be-controlled road segment, and carrying out the pre-processing of the video stream to determine a key frame image; analyzing the key frame image in combination with sensor data, determining traffic data and traffic influence factor values corresponding to the to-be-controlled road section, and inputting the traffic data and the traffic influence factor values into a trained traffic flow prediction model to output a pre-estimated traffic condition corresponding to a preset time period; generating a recommended planning path corresponding to the driving vehicle based on the vehicle driving demand and the estimated traffic condition which are acquired in real time, and optimizing the estimated traffic condition based on the confirmation condition of the driving vehicle on the corresponding recommended planning path; and determining a congestion level corresponding to the optimized pre-estimated traffic condition, and determining a ramp management and control strategy corresponding to the congestion level based on a preset ramp management and control library so as to perform ramp management and control on the toll station according to the ramp management and control strategy.
一种基于人工智能的收费站匝道管控方法、设备及介质
13.06.2025
Patent
Elektronische Ressource
Chinesisch
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |