Trajectory Prediction of Surrounding Vehicles Considering Individual Driving Characteristics

Hanwool Woo, Yonghoon, Yusuke Tamura, Yasuhide Kuroda, Takashi Sugano, Yasunori Yamamoto, Atsushi Yamashita, Hajime Asama

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

We propose a method to predict trajectories of surrounding vehicles considering individual driving characteristics. Trajectory prediction of surrounding vehicles is attracting a lot of attention now, and it is expected to apply to advanced driver assistance systems. However, previous methods perform the trajectory prediction based on common driving patterns even though each driver shows a different driving characteristic. The proposed method focuses on the following behavior behind the preceding vehicle and estimates a driving characteristic of each driver using machine learning techniques. Based on the estimation result, the proposed method adjusts the prediction model and appropriately generates a trajectory. As the result, the performance of trajectory prediction can be dramatically improved.

Original languageEnglish
Pages (from-to)282-288
Number of pages7
JournalInternational Journal of Automotive Engineering
Volume9
Issue number4
DOIs
Publication statusPublished - 2018
Externally publishedYes

Keywords

  • Accident avoidance/collision prediction
  • Intelligent/computer application [c1]
  • Safety

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Fluid Flow and Transfer Processes

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