自動運転車向けハードウェアアクセラレータ：レビュー
Hardware Accelerators for Autonomous Cars: A Review
自動運転車の機械視覚システムに用いられるハードウェアとアルゴリズムの最新研究をレビューし、商用車の技術の長所短所と今後の方向性を議論した論文。
著者: Ruba Islayem, Fatima Alhosani, Raghad Hashem, Afra Alzaabi, Mahmoud Meribout
分類: cs.AR, cs.RO
原文アブストラクト
Autonomous Vehicles (AVs) redefine transportation with sophisticated technology, integrating sensors, cameras, and intricate algorithms. Implementing machine learning in AV perception demands robust hardware accelerators to achieve real-time performance at reasonable power consumption and footprint. Lot of research and development efforts using different technologies are still being conducted to achieve the goal of getting a fully AV and some cars manufactures offer commercially available systems. Unfortunately, they still lack reliability because of the repeated accidents they have encountered such as the recent one which happened in California and for which the Cruise company had its license suspended by the state of California for an undetermined period [1]. This paper critically reviews the most recent findings of machine vision systems used in AVs from both hardware and algorithmic points of view. It discusses the technologies used in commercial cars with their pros and cons and suggests possible ways forward. Thus, the paper can be a tangible reference for researchers who have the opportunity to get involved in designing machine vision systems targeting AV