A Path Prediction Algorithm of Surrounding Vehicles Based on Sensor Fusion for Safe Lane Change

Jihun Kim, Dong Seog Han

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper, we propose a route prediction algorithm for surrounding vehicles for advanced driver assistance system for safe lane change. The proposed algorithm makes it possible to determine whether the lane can be safely changed by recognizing the surrounding environment using radar and camera sensors and predicting the paths of the surrounding vehicles using the linear Kalman filter. The proposed algorithm consists of an input unit from radar and camera sensors, a sensor fusion unit, a path estimation unit of surrounding vehicles using the linear Kalman filter, and a lane change decision unit based on path prediction. In actual vehicle environments, the accuracy of the path prediction for the proposed algorithm is about 95%.

Original languageEnglish
Pages (from-to)828-836
Number of pages9
JournalJournal of Korean Institute of Communications and Information Sciences
Volume45
Issue number5
DOIs
StatePublished - May 2020

Keywords

  • Camera
  • Kalman Filter
  • Path Prediction
  • Radar
  • Sensor Fusion

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