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App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 11

Fusion of distance threshold and bi-tcn for spatio-temporal attention pedestrian trajectory prediction model

Wang Hongxia
Nie Zhenkai
Zhong Qiang
College of Information Science & Engineering, Shenyang Ligong University, Shenyang 110159, China
DOI: 10.19734/j.issn.1001-3695.2024.04.0103

Abstract

In order to solve the problems such as insufficient interaction modeling and low prediction accuracy due to the lack of partial pedestrian modeling ideas, the lack of global vision in time dimension, and the neglect of the diversity of pedestrian interaction modes, this paper proposed an improved model STG-DTBTA based on Social-STGCNN. The model firstly constructed PPM module, and pruned the pedestrians inter links that were not meet constraints such as distance threshold for denoising. Secondly, the model introduced the spatio-temporal attention mechanism. Spatial attention dynamically assigned interactive weights, and set up multiple attention heads to deal with the interaction diversity problem. Temporal attention captured temporal dependencies of temporal data. Finally, the model used Bi-TCN to increase global perspective to capture dynamic patterns and trends in trajectory data, and used gating mechanism to incorporate the bidirectional features. The experimental results on the datasets ETH and UCY showed that compared with Social-STGCNN, ADE and FDE were decreased by an average of 8% and 16% respectively when the number of parameters and the inference time kept close to it. The STG-DTBTA has good interactive modeling ability, model performance and prediction effect.

Foundation Support

辽宁省自然科学基金指导计划项目(2022-MS-276)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.04.0103
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 11

Publish History

[2024-08-05] Accepted Paper

Cite This Article

王红霞, 聂振凯, 钟强. 融合距离阈值和双向TCN的时空注意力行人轨迹预测模型 [J]. 计算机应用研究, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.04.0103. (Wang Hongxia, Nie Zhenkai, Zhong Qiang. Fusion of distance threshold and bi-tcn for spatio-temporal attention pedestrian trajectory prediction model [J]. Application Research of Computers, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.04.0103. )

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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