A Transformer-based Trajectory Prediction Method
Article No.: 126, Pages 1 - 3
Abstract
The periodic trajectories of people provide an insightful and concise explanation over a long moving history, which helps to predict their future movements. In this paper, we present a Transformer based trajectory prediction method to predict the trajectories of people. First, we combine the spatial contexts of a trajectory with the sequential, temporal, and social contexts of a trajectory. Then, we predict the trajectories of people by applying Transformer based model where we multiply the length of query vector and the length of key vector with the scaling factor of the Transformer in order to make the training process more stable. As a result, our proposed Transformer based trajectory prediction model was effective.
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Index Terms
- A Transformer-based Trajectory Prediction Method
Index terms have been assigned to the content through auto-classification.
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Information
Published In
October 2023
1605 pages
ISBN:9781450399906
DOI:10.1145/3570361
- Chairs:
- Xavier Costa,
- Joerg Widmer,
- Co-chairs:
- Diego Perino,
- Domenico Giustiniano,
- Program Chair:
- Haitham Al Hassanieh,
- Program Co-chairs:
- Arash Asadi,
- Landon Cox
Copyright © 2023 ACM.
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Association for Computing Machinery
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Publication History
Published: 02 October 2023
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- Short-paper
Conference
ACM MobiCom '23
Sponsor:
ACM MobiCom '23: 29th Annual International Conference on Mobile Computing and Networking
October 2 - 6, 2023
Madrid, Spain
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