自動運転における行動クローニングモデルの実世界検証
Behavioral Cloning Models Reality Check for Autonomous Driving
行動クローニングで横方向制御を行う知覚システムを実車スケールモデルで実世界検証し、ステアリング角を低誤差でリアルタイム予測できることを示した。
著者: Mustafa Yildirim, Barkin Dagda, Vinal Asodia, Saber Fallah
分類: cs.RO, cs.AI, cs.CV
原文アブストラクト
How effective are recent advancements in autonomous vehicle perception systems when applied to real-world autonomous vehicle control? While numerous vision-based autonomous vehicle systems have been trained and evaluated in simulated environments, there is a notable lack of real-world validation for these systems. This paper addresses this gap by presenting the real-world validation of state-of-the-art perception systems that utilize Behavior Cloning (BC) for lateral control, processing raw image data to predict steering commands. The dataset was collected using a scaled research vehicle and tested on various track setups. Experimental results demonstrate that these methods predict steering angles with low error margins in real-time, indicating promising potential for real-world applications.
