Sensor fusion for vehicle tracking with camera and radar sensor

Kyeong Eun Kim, Chang Joo Lee, Dong Sung Pae, Myo Taeg Lim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

In recent years, as demands for the vehicle safety and autonomous driving of the automobile industry have increased, it becomes important to more accurately recognize the position and velocity of surrounding vehicles. In this paper, heuristic fusion with adaptive gating and track to track fusion are applied to track fusion of camera and radar sensor for forward vehicle tracking system and the two algorithms are compared. To compare the two algorithms, simulation was carried out in 10 scenarios and the accuracy of sensor fusion results was measured with optimal subpattern assignment (OSPA) metric. The results of this metric are compared to show that the track to track fusion is superior to the adaptive gating for the target estimation.

Original languageEnglish
Title of host publicationICCAS 2017 - 2017 17th International Conference on Control, Automation and Systems - Proceedings
PublisherIEEE Computer Society
Pages1075-1077
Number of pages3
Volume2017-October
ISBN (Electronic)9788993215137
DOIs
Publication statusPublished - 2017 Dec 13
Event17th International Conference on Control, Automation and Systems, ICCAS 2017 - Jeju, Korea, Republic of
Duration: 2017 Oct 182017 Oct 21

Other

Other17th International Conference on Control, Automation and Systems, ICCAS 2017
CountryKorea, Republic of
CityJeju
Period17/10/1817/10/21

Keywords

  • Adaptive gating
  • Data association
  • Sensor Fusion
  • Track to track fusion
  • Vehicle tracking

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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