基于时空交互图注意力网络的多模态车辆轨迹预测模型
A Multimodal Vehicle Trajectory Prediction Model Based on Spatio-Temporal Interaction Graph Attention Network
摘要
Abstract
In the field of autonomous driving,trajectory prediction of traffic participants is a critical yet challenging problem,where accurately capturing the complex spatio-temporal features within trajectory data is essential for precise prediction.To address the issues of insufficient spatio-temporal feature extraction and multimodal vehicle trajectory prediction,a multimodal vehicle trajectory prediction model based on spatio-temporal feature interaction—STGA is proposed.Firstly,a dynamic graph neural network and a fusion-attention-based spatio-temporal Transformer network are utilized to capture both the spatial interaction features and temporal dependencies of vehicles within the target area.Next,a gated unit for feature fusion is designed to effectively merge spatio-temporal features,followed by the decoder generating a probability distribution for future trajectories of vehicles in the target region.Finally,the proposed model is evaluated on public dataset and compared against baseline models.Experimental results demonstrate that the proposed model outperforms other baseline methods,achieving a 32.03%reduction in Average Displacement Error(ADE)and a 14%reduction in Final Displacement Error(FDE)compared to the comparison models.关键词
车辆运动预测/时空交互/图注意力网络/自动驾驶/深度学习Key words
vehicle motion prediction/spatio-temporal interaction/graph attention networks/autonomous driving/deep learning分类
信息技术与安全科学引用本文复制引用
李庆,韩楠,李任杰,杨博渊,相东升,张杉彬,王家伟,吴绍伟,黄晨..基于时空交互图注意力网络的多模态车辆轨迹预测模型[J].无线电工程,2025,55(2):254-263,10.基金项目
国家自然科学基金(62272066) （62272066）
四川省科技计划(2025ZNSFSC0044,2025YFHZ0194,2024YFFK0413) （2025ZNSFSC0044,2025YFHZ0194,2024YFFK0413）
成都市技术创新研发项目重点项目(2024-YF08-00029-GX) （2024-YF08-00029-GX）
成都市区域科技创新合作项目(2025-YF11-00031-HZ,2025-YF11-00050-HZ,2023-YF11-00020-HZ) （2025-YF11-00031-HZ,2025-YF11-00050-HZ,2023-YF11-00020-HZ）
成都市技术创新研发项目(2024-YF05-01217-SN) （2024-YF05-01217-SN）
网络空间安全教育部重点实验室及河南省网络空间态势感知重点实验室开放基金课题(KLCS20240106) （KLCS20240106）
大学生创新创业训练计划项目(202410621195,202410621183)National Natural Science Foundation of China(62272066) （202410621195,202410621183）
Sichuan Science and Technology Program(2025ZNSFSC0044,2025YFHZ0194,2024YFFK0413) （2025ZNSFSC0044,2025YFHZ0194,2024YFFK0413）
Chengdu Technological Innovation Research and Development Major Project(2024-YF08-00029-GX) （2024-YF08-00029-GX）
Chengdu Regional Science and Technology Innovation Cooperation Project(2025-YF11-00031-HZ,2025-YF11-00050-HZ,2023-YF11-00020-HZ) （2025-YF11-00031-HZ,2025-YF11-00050-HZ,2023-YF11-00020-HZ）
Chengdu Technological Innovation Research and Development Project(2024-YF05-01217-SN) （2024-YF05-01217-SN）
Open Foundation of Key Laboratory of Cyberspace Security,Minis-try of Education of China and Henan Key Laboratory of Cyberspace Situation Awareness(KLCS20240106) （KLCS20240106）
College Student Innovation and Entrepreneur-ship Training Program Project(202410621195,202410621183) （202410621195,202410621183）
