首页> 外国专利> METHODS AND SYSTEMS FOR TRAJECTORY FORECASTING WITH RECURRENT NEURAL NETWORKS USING INERTIAL BEHAVIORAL ROLLOUT

METHODS AND SYSTEMS FOR TRAJECTORY FORECASTING WITH RECURRENT NEURAL NETWORKS USING INERTIAL BEHAVIORAL ROLLOUT

机译:使用惯性行为卷展处理经常性神经网络的轨迹预测方法和系统

摘要

Systems and methods for forecasting trajectories of objects. The method includes obtaining a prediction model trained to predict future trajectories of objects. The prediction model is trained over a first prediction horizon selected to encode inertial constraints in a predicted trajectory and over a second prediction horizon selected to encode behavioral constraints in the predicted trajectory. The method also include generating a planned trajectory of an autonomous vehicle by receiving state data corresponding to the autonomous vehicle, receiving perception data corresponding to an object, predicting a future trajectory of the object based on the perception data and the prediction model, and generating the planned trajectory of the autonomous vehicle based on the future trajectory of the object and the state data.
机译:用于预测物体轨迹的系统和方法。 该方法包括获得训练的预测模型以预测对象的未来轨迹。 预测模型在选择以在预测的轨迹中的惯性约束中和选择以在预测的轨迹中编码行为约束的第二预测地平线中编码惯性约束的第一预测地平线训练。 该方法还包括通过接收与自主车辆对应的状态数据来生成自主车辆的计划轨迹,接收对对象的感知数据,基于感知数据和预测模型预测对象的未来轨迹,并生成 基于对象的未来轨迹和国家数据的自主车辆的计划轨迹。

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