Novel Vehicle Bounding Box Tracking Using a Low-End 3D Laser Scanner

Jhonghyun An, Euntai Kim

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Vehicle bounding box tracking (VBBT) is a new problem that is becoming increasingly important in autonomous driving. It is defined as a problem in which not only the position but also the size of a target vehicle is estimated using a sensor. In this paper, novel VBBT using a low-end three-dimensional (3D) laser scanner is proposed. Compared to previous methods, the proposed VBBT has three distinctions: (1) the center of a rectangular vehicle is defined as its position, and the motion model that uses the center of the vehicle as the state is developed; (2) a new measurement model is proposed that models the measured size of the target vehicle as a sample from a uniform distribution; and (3) a Bayesian filter for the proposed motion and measurement model is developed and it is named as the Pareto Kalman filter (PKF). Finally, the proposed method is applied to six scenarios, and its validity is demonstrated through experimentation.

Original languageEnglish
Article number9098054
Pages (from-to)3403-3419
Number of pages17
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number6
Publication statusPublished - 2021 Jun

Bibliographical note

Funding Information:
Manuscript received October 16, 2019; revised March 10, 2020; accepted May 8, 2020. Date of publication May 21, 2020; date of current version June 2, 2021. This work was supported by the National Research Foundation of Korea (NRF) through the Basic Science Research Program funded by the Ministry of Education, Science, and Technology under Grant NRF-2019R1A2C1007153. The Associate Editor for this article was L. M. Bergasa. (Corresponding author: Euntai Kim.) The authors are with the School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea (e-mail:; Digital Object Identifier 10.1109/TITS.2020.2994624

Publisher Copyright:
© 2000-2011 IEEE.

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications


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