Graph convolutional neural network model and vehicle trajectory prediction method using same
一种卷积神经网络、车辆轨迹的技术,应用在车辆智能驾驶领域,能够解决难以表达出隐式关系等问题,达到提高泛化能力、避免过拟合、提高鲁棒性的效果
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[0015] The present invention will be further described below in conjunction with accompanying drawing.
[0016] Step1: Model building
[0017] 1. Model input
[0018] The input feature value of trajectory prediction contains four necessary components, including the historical trajectory of the predicted vehicle, the historical trajectory of the surrounding vehicles of the predicted vehicle, the time TTC when the predicted vehicle and surrounding vehicles reach the collision point, and the vehicle behavior at each moment.
[0019] (1) The historical trajectory of the predicted vehicle
[0020] The historical trajectory sequence of the predicted vehicle can be expressed as:
[0021] x ego ={x (t-S) ,...,x (t-1) ,x (t)}
[0022] S is the length of the historical trajectory sequence, x (t) Indicates the historical trajectory of the vehicle under test, and t is the current moment, where:
[0023]
[0024] is the horizontal and vertical coordinates of the predicted car...
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