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Updated: Feb 19, 2026

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior
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自動運転車両の意思決定は,様々な危険な歩行者横断行動の下で行われる

Xu Chen1, Hao Wang1

  • 1Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 211189, China; School of Transportation, Southeast University, Nanjing 211189, China.

Accident; analysis and prevention
|February 17, 2026
PubMed
まとめ

自動運転車両 (AV) は,新しいリスク認識の深層強化学習 (DRL) フレームワークを使用して,危険な歩行者との複雑な都市交通をナビゲートすることができます. このアプローチは,挑戦的で現実的な運転シナリオにおいて,安全性と交通効率を高めます.

キーワード:
自動運転車両は自動運転車である.意思決定 意思決定深層強化学習 (DEP) による学習です.気を散らすものジェイウォーカーズ (Jaywalkers) とはオックルションのシナリオ

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