単眼魚眼カメラによるエンドツーエンド車両追従システム
End-to-end Autonomous Vehicle Following System using Monocular Fisheye Camera
単眼魚眼カメラのみを用いたエンドツーエンドの車両追従フレームワークを提案し、意味マスクと動的サンプリングで先行車追従を高精度化、実車実験で従来手法を上回る性能を示した。
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著者: Jiale Zhang, Yeqiang Qian, Tong Qin, Mingyang Jiang, Siyuan Chen, Ming Yang
分類: cs.RO
原文アブストラクト
The increase in vehicle ownership has led to increased traffic congestion, more accidents, and higher carbon emissions. Vehicle platooning is a promising solution to address these issues by improving road capacity and reducing fuel consumption. However, existing platooning systems face challenges such as reliance on lane markings and expensive high-precision sensors, which limits their general applicability. To address these issues, we propose a vehicle following framework that expands its capability from restricted scenarios to general scenario applications using only a camera. This is achieved through our newly proposed end-to-end method, which improves overall driving performance. The method incorporates a semantic mask to address causal confusion in multi-frame data fusion. Additionally, we introduce a dynamic sampling mechanism to precisely track the trajectories of preceding vehicles. Extensive closed-loop validation in real-world vehicle experiments demonstrates the system's ability to follow vehicles in various scenarios, outperforming traditional multi-stage algorithms. This makes it a promising solution for cost-effective autonomous vehicle platooning. A complete real-world vehicle experiment is available at https://youtu.be/zL1bcVb9kqQ.
