The invention relates to a vulnerable traffic participant trajectory prediction method based on an LSTM model, and the method is characterized in that the method comprises the following steps: 1, selecting vulnerable traffic participants and vehicles in a zebra crossing region under the condition of mixed driving of people and vehicles, and carrying out the early-stage investigation; step 2, acquiring motion state information, individual feature information and interaction scene information of street-crossing vulnerable traffic participants; 3, establishing an LSTM (Long Short Term Memory) model, and training the LSTM model; and step 4, performing trajectory prediction on the street-crossing vulnerable traffic participants through the trained LSTM model, and obtaining predicted trajectories of the street-crossing vulnerable traffic participants within a first preset duration in the future, compared with the prior art, the method has the advantages of improving the street-crossing safety of the vulnerable traffic participants, improving the traffic capacity of the road and the like.
本发明涉及一种基于LSTM模型的弱势交通参与者轨迹预测方法,其特征在于,该方法包括以下步骤:步骤1:选取弱势交通参与者和车辆在人车混行情况下的斑马线区域进行前期调查;步骤2:获取过街弱势交通参与者运动状态信息、过街弱势交通参与者个体特征信息及交互场景信息;步骤3:建立LSTM模型,并对LSTM模型进行训练;步骤4:通过训练后的LSTM模型对过街弱势交通参与者进行轨迹预测,获取未来第一预设时长内过街弱势交通参与者的预测轨迹,与现有技术相比,本发明具有提高弱势交通参与者过街的安全性和提高道路的通行能力等优点。
LSTM model-based vulnerable traffic participant trajectory prediction method
一种基于LSTM模型的弱势交通参与者轨迹预测方法
2022-05-06
Patent
Elektronische Ressource
Chinesisch
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