自動運転車の意思決定向けデータセットに関するサーベイ
A Survey on Datasets for Decision-making of Autonomous Vehicle
自動運転の意思決定に用いられる既存データセットを車両・環境・ドライバー関連の3種に分類し、センサやアノテーション、走行シナリオなどの特徴と応用可能性を整理したサーベイ。
著者: Yuning Wang, Zeyu Han, Yining Xing, Shaobing Xu, Jianqiang Wang
分類: cs.RO, cs.AI, cs.MA
原文アブストラクト
Autonomous vehicles (AV) are expected to reshape future transportation systems, and decision-making is one of the critical modules toward high-level automated driving. To overcome those complicated scenarios that rule-based methods could not cope with well, data-driven decision-making approaches have aroused more and more focus. The datasets to be used in developing data-driven methods dramatically influences the performance of decision-making, hence it is necessary to have a comprehensive insight into the existing datasets. From the aspects of collection sources, driving data can be divided into vehicle, environment, and driver related data. This study compares the state-of-the-art datasets of these three categories and summarizes their features including sensors used, annotation, and driving scenarios. Based on the characteristics of the datasets, this survey also concludes the potential applications of datasets on various aspects of AV decision-making, assisting researchers to find appropriate ones to support their own research. The future trends of AV dataset development are summarized.
