Goal estimation of mandatory lane changes based on interaction between drivers

Hanwool Woo, Mizuki Sugimoto, Hirokazu Madokoro, Kazuhito Sato, Yusuke Tamura, Atsushi Yamashita, Hajime Asama

Research output: Contribution to journalArticle

Abstract

In this paper, we propose a novel method to estimate a goal of surround vehicles to perform a lane change at a merging section. Recently, autonomous driving and advance driver-assistance systems are attracting great attention as a solution to substitute human drivers and to decrease accident rates. For example, a warning system to alert a lane change performed by surrounding vehicles to the front space of the host vehicle can be considered. If it is possible to forecast the intention of the interrupting vehicle in advance, the host driver can easily respond to the lane change with sufficient reaction time. This paper assumes a mandatory situation where two lanes are merged. The proposed method assesses the interaction between the lane-changing vehicle and the host vehicle on the mainstream lane. Then, the lane-change goal is estimated based on the interaction under the assumption that the lane-changing driver decides to minimize the collision risk. The proposed method applies the dynamic potential field method, which changes the distribution according to the relative speed and distance between two subject vehicles, to assess the interaction. The performance of goal estimation is evaluated using real traffic data, and it is demonstrated that the estimation can be successfully performed by the proposed method.

Original languageEnglish
Article number3289
JournalApplied Sciences (Switzerland)
Volume10
Issue number9
DOIs
Publication statusPublished - 2020 May 1

Keywords

  • Autonomous driving
  • Goal estimation
  • Lane change
  • Trajectory prediction

ASJC Scopus subject areas

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

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