協調車両アプリケーションのための操縦ベース都市走行データセットとモデル
A Maneuver-based Urban Driving Dataset and Model for Cooperative Vehicle Applications
自動運転車と手動運転車が共存する都市環境向けに、実走行で収集した操縦（マヌーバ）単位のデータセットを構築し、操縦パターンを学習して分類・予測に使えるモデルを提案した。
著者: Behrad Toghi, Divas Grover, Mahdi Razzaghpour, Rajat Jain, Rodolfo Valiente, Mahdi Zaman, Ghayoor Shah, Yaser P. Fallah
分類: eess.SP, cs.RO
原文アブストラクト
Short-term future of automated driving can be imagined as a hybrid scenario in which both automated and human-driven vehicles co-exist in the same environment. In order to address the needs of such road configuration, many technology solutions such as vehicular communication and predictive control for automated vehicles have been introduced in the literature. Both aforementioned solutions rely on driving data of the human driver. In this work, we investigate the currently available driving datasets and introduce a real-world maneuver-based driving dataset that is collected during our urban driving data collection campaign. We also provide a model that embeds the patterns in maneuver-specific samples. Such model can be employed for classification and prediction purposes.
