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Algorithm Research & Explore
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1029-1033

Model of predicting motion trajectory of connected vehicles based on Informer algorithm

Zhao Dongyu1,2
Wang Zhijian1,2
Song Chenglong1,2
1. School of Electrical & Control Engineering, North China University of Technology, Beijing 100144, China
2. Beijing Key Laboratory of Intelligent Control Technology for Urban Road Traffic, Beijing 100144, China

Abstract

Autonomous vehicle can calculate the movement track of surrounding vehicles according to the track prediction algorithm, 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 Informer 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 Informer 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 trajectory 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.

Foundation Support

国家自然科学基金资助项目(72071003)
北京市教育委员会科研计划项目(110052971921/023)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.08.0375
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 4
Section: Algorithm Research & Explore
Pages: 1029-1033
Serial Number: 1001-3695(2024)04-010-1029-05

Publish History

[2023-11-03] Accepted Paper
[2024-04-05] Printed Article

Cite This Article

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. (Zhao Dongyu, Wang Zhijian, Song Chenglong. Model of predicting motion trajectory of connected vehicles based on Informer algorithm [J]. Application Research of Computers, 2024, 41 (4): 1029-1033. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


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