The invention relates to the technical field of vehicle control, in particular to an unmanned vehicle control method based on deep learning, and the method comprises the following steps: collecting the multi-modal data of weak participants in a road environment in real time, and recognizing the weak participants; the behaviors of the weak participants at the next moment are predicted through multi-dimensional information fusion, and behavior intention prediction of the weak participants is carried out; the path planning and control strategy of the vehicle is adjusted in real time through the self-adaptive decision control module; and when the predicted behavior intention of the weak participant has high uncertainty or potential risk, an emergency avoidance mechanism is automatically triggered, the risk level of the current traffic environment is dynamically evaluated, an optimal avoidance path is generated, and emergency stop or detour operation is executed. According to the method, double guarantees of high-dimensional analysis of behavior intentions of participants and real-time control of vehicles are combined, and the driving safety in a complex traffic scene is ensured.
本发明涉及车辆控制技术领域,具体涉及一种基于深度学习的无人驾驶车辆控制方法,包括以下步骤:实时采集道路环境中的弱小参与者的多模态数据,识别弱小参与者;通过多维信息融合,预测其下一时刻的弱小参与者行为,进行弱小参与者的行为意图预测;通过自适应决策控制模块对车辆的路径规划和控制策略进行实时调整;当预测到的弱小参与者行为意图存在高度不确定性或潜在风险时,自动触发紧急规避机制,动态评估当前交通环境的风险等级,生成最佳规避路径并执行紧急停车或绕行操作,本发明,结合了对参与者行为意图的高维度分析与车辆实时控制的双重保障,确保复杂交通场景下的行车安全性。
Unmanned vehicle control method based on deep learning
一种基于深度学习的无人驾驶车辆控制方法
2025-01-10
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 / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06V |
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