计算机应用研究2024，Vol.41Issue(4)：1029-1033,5.DOI:10.19734/j.issn.1001-3695.2023.08.0375
基于Informer算法的网联车辆运动轨迹预测模型
Model of predicting motion trajectory of connected vehicles based on Informer algorithm
摘要
Abstract
Autonomous vehicle can calculate the movement track of surrounding vehicles according to the track prediction al-gorithm,and make response to reduce driving risk,while the traditional track prediction model will produce large errors in the case of long-term series prediction.To address this issue,this paper proposed a trajectory prediction model based on the Infor-mer algorithm,and used the publicly available dataset NGSIM to conduct experimental analysison.Firstly,it filtered the original data by using symmetric exponential moving average method(sEMA),and added a joint normalization layer to the original In-former encoder to extract features from different vehicles,reducing the motion error between different vehicles,and improving the prediction accuracy by considering the speed information of the vehicle itself and the vehicle movement information of the surrounding environment.Finally,it got the vehicle trajectory distribution at the future time through the decoder.The results show that the trajectory prediction error of the model is less than 0.5 m.Through the analysis of MAE and MSE results of tra-jectory prediction,when the prediction time exceeds 0.3 s,the trajectory prediction effect of Informer model is obviously better than other algorithms,which verifies the effectiveness of the model and algorithm.关键词
智能交通控制/自动驾驶车辆/轨迹数据预测/Informer模型/注意力模型/特征提取Key words
intelligent traffic control/autonomous vehicles/trajectory data prediction/Informer model/attention model/feature extraction分类
交通工程引用本文复制引用
赵懂宇,王志建,宋程龙..基于Informer算法的网联车辆运动轨迹预测模型[J].计算机应用研究,2024,41(4):1029-1033,5.基金项目
国家自然科学基金资助项目(72071003) （72071003）
北京市教育委员会科研计划项目(110052971921/023) （110052971921/023）
