MOTION PREDICTION OF BICYCLISTS IN URBAN ENVIRONMENTS BASED ON LIDAR DATA
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- 本サイト上にてダウンロード・閲覧可
- 形態
- 価格
- 一般価格(税込):¥1,100 会員価格(税込):¥880
- 文献番号
- 20219030
- 文献・情報種別
- その他の国際会議
- 掲載ページ
- 1-6(Total 6 p)
- 発行年月
- 2021年 9月
- 出版社
- (公社)自動車技術会
- 言語
- 英語
書誌事項
著者(英) | 1) Adrian M. Sonka, 2) Silvia Thal, 3) Roman Henze |
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勤務先(英) | 1) Technische Universität Braunschweig, 2) Technische Universität Braunschweig, 3) Technische Universität Braunschweig |
抄録(英) | Ensuring road safety for bicyclists through an improvement of the foresight of automated vehicles by anticipating critical behavior is a remaining challenge in research and development. A situation adaptive motion planning based on this information can reduce accidents with these vulnerable road users. Our work utilizes machine learning methods for a bicyclist motion prediction, applied to laser scanner data recorded with an own measurement vehicle. Different configurations of multilayer perceptron networks, applied for polynomial coefficient estimation as well as long short-term memory networks are compared and evaluated on a quantitive and qualitative level, surpassing accuracy levels of a physical baseline prediction model. 翻訳 |