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Toward Unified Practices in Trajectory Prediction Research on Bird's-Eye-View Datasets

Westny, Theodor ; Olofsson, Björn LU and Frisk, Erik (2025) 36th IEEE Intelligent Vehicles Symposium, IV 2025 In IEEE Intelligent Vehicles Symposium, Proceedings p.83-89
Abstract

The availability of high-quality datasets is crucial for developing behavior prediction algorithms in autonomous vehicles. This paper highlights the need to standardize the use of certain datasets for motion forecasting research to simplify comparative analysis and proposes a set of tools and practices to achieve this. Drawing on extensive experience and a comprehensive review of current literature, we summarize our proposals for preprocessing, visualization, and evaluation in the form of an open-sourced toolbox designed for researchers working on trajectory prediction problems. The clear specification of necessary preprocessing steps and evaluation metrics is intended to alleviate development efforts and facilitate the comparison of... (More)

The availability of high-quality datasets is crucial for developing behavior prediction algorithms in autonomous vehicles. This paper highlights the need to standardize the use of certain datasets for motion forecasting research to simplify comparative analysis and proposes a set of tools and practices to achieve this. Drawing on extensive experience and a comprehensive review of current literature, we summarize our proposals for preprocessing, visualization, and evaluation in the form of an open-sourced toolbox designed for researchers working on trajectory prediction problems. The clear specification of necessary preprocessing steps and evaluation metrics is intended to alleviate development efforts and facilitate the comparison of results across different studies. The toolbox is available at: https://github.com/westny/dronalize.

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Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
IV 2025 - 36th IEEE Intelligent Vehicles Symposium
series title
IEEE Intelligent Vehicles Symposium, Proceedings
pages
7 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
36th IEEE Intelligent Vehicles Symposium, IV 2025
conference location
Cluj-Napoca, Romania
conference dates
2025-06-22 - 2025-06-25
external identifiers
  • scopus:105014242174
ISSN
1931-0587
2642-7214
ISBN
9798331538033
DOI
10.1109/IV64158.2025.11097573
project
ELLIIT B14: Autonomous Force-Aware Swift Motion Control
RobotLab LTH
language
English
LU publication?
yes
additional info
Publisher Copyright: © 2025 IEEE.
id
539c42be-8b7a-492c-a2d2-4e07ea73c801
alternative location
https://arxiv.org/abs/2405.00604
date added to LUP
2025-09-08 18:14:31
date last changed
2025-09-09 14:22:32
@inproceedings{539c42be-8b7a-492c-a2d2-4e07ea73c801,
  abstract     = {{<p>The availability of high-quality datasets is crucial for developing behavior prediction algorithms in autonomous vehicles. This paper highlights the need to standardize the use of certain datasets for motion forecasting research to simplify comparative analysis and proposes a set of tools and practices to achieve this. Drawing on extensive experience and a comprehensive review of current literature, we summarize our proposals for preprocessing, visualization, and evaluation in the form of an open-sourced toolbox designed for researchers working on trajectory prediction problems. The clear specification of necessary preprocessing steps and evaluation metrics is intended to alleviate development efforts and facilitate the comparison of results across different studies. The toolbox is available at: https://github.com/westny/dronalize.</p>}},
  author       = {{Westny, Theodor and Olofsson, Björn and Frisk, Erik}},
  booktitle    = {{IV 2025 - 36th IEEE Intelligent Vehicles Symposium}},
  isbn         = {{9798331538033}},
  issn         = {{1931-0587}},
  language     = {{eng}},
  pages        = {{83--89}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Intelligent Vehicles Symposium, Proceedings}},
  title        = {{Toward Unified Practices in Trajectory Prediction Research on Bird's-Eye-View Datasets}},
  url          = {{http://dx.doi.org/10.1109/IV64158.2025.11097573}},
  doi          = {{10.1109/IV64158.2025.11097573}},
  year         = {{2025}},
}