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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages838-843
Number of pages6
ISBN (Electronic)9781509018970
DOIs
Publication statusPublished - 2017 Feb 6
Externally publishedYes
Event2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Budapest, Hungary
Duration: 2016 Oct 92016 Oct 12

Publication series

Name2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings

Other

Other2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016
Country/TerritoryHungary
CityBudapest
Period16/10/916/10/12

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Control and Optimization
  • Human-Computer Interaction

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