The invention discloses an end-to-end automatic driving decision planning model and device combining a vectorized map and multi-task feature embedding. The end-to-end automatic driving decision planning model comprises six task branches of different modules such as perception, decision and control. An end-to-end automatic driving framework is utilized to reduce errors between different model transmissions, and a multi-task constraint mode is utilized to improve the fitting ability of the model. Vectorized map and aerial view target detection are combined to serve as perception representation of a multi-task model, dynamic and static target information needed in aerial view space is provided, environment perception information and decision navigation point output are unified to the same space, and model prediction precision is improved. Information transmission is performed by using a cross attention mechanism between different tasks, training conflicts caused by simple sharing of feature maps in a traditional multi-task model are overcome, efficient coupling between different tasks is realized, and model prediction precision is improved.
本发明公开了一种结合向量化地图与多任务特征嵌入的端到端自动驾驶决策规划模型与设备,包含感知、决策以及控制等不同模块的六个任务分支。利用端到端自动驾驶框架减少不同模型传递之间的误差,利用多任务约束的方式增加模型的拟合能力。结合向量化地图与鸟瞰图目标检测作为多任务模型的感知表征,提供了鸟瞰图空间下所需要的动态以及静态目标信息,同时将环境感知信息与决策的导航点输出统一到相同空间,提升模型预测精度。利用不同任务之间的交叉注意力机制进行信息传递,克服传统多任务模型中简单共享特征图导致的训练冲突,实现不同任务之间的高效耦合,提升模型预测精度。
Vectorized map and multi-task feature embedding combined end-to-end automatic driving decision planning model and device
一种结合向量化地图与多任务特征嵌入的端到端自动驾驶决策规划模型与设备
2024-12-13
Patent
Electronic Resource
Chinese
IPC: | G06V / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / 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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