The invention provides a trajectory prediction method, device and equipment. The method comprises the following steps: inputting an obtained first target feature of a target moving object to a trained intention simulator to obtain first prediction data of K future moments; determining a target position of the future moment based on the Gaussian parameter of the candidate position corresponding to the future moment, and determining a second target feature of the target moving object based on the target positions of the K future moments; inputting the second target feature into a trained trajectory predictor to obtain second prediction data of K future moments; and determining a target mode of the future moment based on the prediction probability of each mode corresponding to the future moment, determining a prediction position of the future moment based on the Gaussian parameter of the candidate position corresponding to the future moment, and determining a prediction trajectory of the target moving object based on the target modes and the prediction positions of the K future moments. According to the technical scheme, the accurate and reliable prediction trajectory can be obtained, and the quality of the prediction trajectory can be improved.
本申请提供一种轨迹预测方法、装置及设备,该方法包括:将目标运动对象的已获取的第一目标特征输入给已训练的意图模拟器得到K个未来时刻的第一预测数据;基于未来时刻对应的候选位置的高斯参数确定该未来时刻的目标位置,基于K个未来时刻的目标位置确定目标运动对象的第二目标特征;将第二目标特征输入给已训练的轨迹预测器得到K个未来时刻的第二预测数据;基于未来时刻对应的每个模态的预测概率确定该未来时刻的目标模态,基于未来时刻对应的候选位置的高斯参数确定该未来时刻的预测位置,基于K个未来时刻的目标模态和预测位置确定目标运动对象的预测轨迹。通过本申请的技术方案,能够得到准确可靠的预测轨迹,并能够提升预测轨迹的质量。
Trajectory prediction method, device and equipment
一种轨迹预测方法、装置及设备
2023-08-29
Patent
Electronic Resource
Chinese
IPC: | B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |
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