Spatial Attention for Autonomous Decision-making in Highway Scene

Shuwei Zhang, Yutian Wu, Harutoshi Ogai

研究成果: Conference contribution

抄録

Automated decision making is still a significant challenge to realize fully autonomous driving. A common method that encoding surrounding vehicles in a grid map is used to describe observation space for decision making algorithm. It preserves vehicles spatial characteristics. But commonly in human driving, distinct position and speed surrounding vehicles contribute differently to make decision. We introduce a spatial attention module to calculate weights for each vehicle and integrate the attention mechanism into Deep Q network to make decision actions. The agent, ego vehicle, is trained in a simulated highway environment. Simulation results show the proposed method can get significant performance gains compared with other deep reinforcement learning methods by using two kinds of metrics.

本文言語English
ホスト出版物のタイトル2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1435-1440
ページ数6
ISBN(電子版)9781728110899
出版ステータスPublished - 2020 9 23
イベント59th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2020 - Chiang Mai, Thailand
継続期間: 2020 9 232020 9 26

出版物シリーズ

名前2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2020

Conference

Conference59th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2020
国/地域Thailand
CityChiang Mai
Period20/9/2320/9/26

ASJC Scopus subject areas

  • 制御と最適化
  • 器械工学
  • コンピュータ ビジョンおよびパターン認識
  • 信号処理
  • 決定科学(その他)
  • 産業および生産工学

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