Lane-changing feature extraction using multisensor integration

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

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

We propose a feature extraction method for lane changes of other traffic participants. 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 feature extraction method using the multisensor system which consists of a position sensor and a laser scanner with line markings information. For a lane change prediction of other traffic participants, the most effective features are a lateral position and velocity with respect to a center line. We installed the sensor system to the primary vehicle and measured positions of other traffic participants while the primary vehicle drives on a highway. We extracted the features as the distance with respect to the center line and the lateral velocity of other vehicles using the measurement data. We confirmed that our feature extraction method has an enough accuracy for the lane change prediction.

本文言語English
ホスト出版物のタイトルICCAS 2016 - 2016 16th International Conference on Control, Automation and Systems, Proceedings
出版社IEEE Computer Society
ページ1633-1636
ページ数4
ISBN(電子版)9788993215120
DOI
出版ステータスPublished - 2016 1 24
外部発表はい
イベント16th International Conference on Control, Automation and Systems, ICCAS 2016 - Gyeongju, Korea, Republic of
継続期間: 2016 10 162016 10 19

出版物シリーズ

名前International Conference on Control, Automation and Systems
0
ISSN(印刷版)1598-7833

Conference

Conference16th International Conference on Control, Automation and Systems, ICCAS 2016
CountryKorea, Republic of
CityGyeongju
Period16/10/1616/10/19

ASJC Scopus subject areas

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

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