The invention discloses a trajectory control method and device, a vehicle and a storage medium. The method comprises the following steps: acquiring current environment data; inputting the current environment data into a convolutional neural network-support vector machine (CNN-SVM) model, so as to output an output vector composed of predicted values of at least two behavior decisions through the CNN-SVM model; and determining a target behavior decision according to the output vector, and controlling the driving track of the vehicle according to the target behavior decision. According to the technical scheme, the defects that in the automatic driving process of the intelligent vehicle, self-adjustment cannot be achieved based on rule learning, and scene coverage is incomplete are overcome, and the behavior decision reliability and driving safety of the automatic driving vehicle are improved.
本发明公开了一种轨迹控制方法、装置、车辆及存储介质。该方法包括:获取当前环境数据;将所述当前环境数据输入至卷积神经网络‑支持向量机模型CNN‑SVM模型,以通过所述CNN‑SVM模型输出由至少两种行为决策的预测值组成的输出向量;根据所述输出向量确定目标行为决策,并按照所述目标行为决策控制车辆的行驶轨迹。上述技术方案解决了智能车辆在自动驾驶过程中基于规则学习不能自调整、场景覆盖不完全等缺点,提高了自动驾驶车辆的行为决策可靠性和行车安全性。
Track control method and device, vehicle and storage medium
轨迹控制方法、装置、车辆及存储介质
2022-04-05
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 |
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