Dynamic potential-model-based feature for lane change prediction

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

研究成果: Conference contribution

14 被引用数 (Scopus)

抄録

We propose a prediction method for lane changes in other vehicles. According to previous research, over 90 % of car crashes are caused by human mistakes, and lane changes are the main factor. Therefore, if an intelligent system can predict a lane change and alarm a driver before another vehicle crosses the center line, this can contribute to reducing the accident rate. The main contribution of this work is to propose a new feature describing the relationship of a vehicle to adjacent vehicles. We represent the new feature using a dynamic characteristic potential field that changes the distribution depending on the relative number of adjacent vehicles. The new feature addresses numerous situations in which lane changes are made. Adding the new feature can be expected to improve prediction performance. We trained the prediction model and evaluated the performance using a real traffic dataset with over 900 lane changes, and we confirmed that the proposed method outperforms previous methods in terms of both accuracy and prediction time.

本文言語English
ホスト出版物のタイトル2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ838-843
ページ数6
ISBN(電子版)9781509018970
DOI
出版ステータスPublished - 2017 2月 6
外部発表はい
イベント2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Budapest, Hungary
継続期間: 2016 10月 92016 10月 12

出版物シリーズ

名前2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings

Other

Other2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016
国/地域Hungary
CityBudapest
Period16/10/916/10/12

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識
  • 人工知能
  • 制御と最適化
  • 人間とコンピュータの相互作用

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