본문 바로가기
  • Home

Localization of Mobile Users with the Improved Kalman Filter Algorithm using Smart Traffic Lights in Self-driving Environments

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2019, 24(5), pp.67-72
  • DOI : 10.9708/jksci.2019.24.05.067
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : March 8, 2019
  • Accepted : April 30, 2019
  • Published : May 31, 2019

JungJuHo 1 Jung-Eun Song 1 AHN JUN HO 1

1한국교통대학교

Accredited

ABSTRACT

The self-driving cars identify appropriate navigation paths and obstacles to arrive at their destinations without human control. The autonomous cars are capable of sensing driving environments to improve driver and pedestrian safety by sharing with neighbor traffic infrastructure. In this paper, we have focused on pedestrian protection and have designed an improved localization algorithm to track mobile users on roads by interacting with smart traffic lights in vehicle environments. We developed smart traffic lights with the RSSI sensor and built the proposed method by improving the Kalman filter algorithm to localize mobile users accurately. We successfully evaluated the proposed algorithm to improve the mobile user localization with deployed five smart traffic lights.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.