Abstract
The availability of high-quality datasets is crucial for the development of behavior prediction algorithms in autonomous vehicles. This paper highlights the need for standardizing the use of certain datasets for motion forecasting research to simplify comparative analysis and proposes a set of tools and practices to achieve this. Drawing on extensive experience and a comprehensive review of current literature, we summarize our proposals for preprocessing, visualizing, and evaluation in the form of an open-sourced toolbox designed for researchers working on trajectory prediction problems. The clear specification of necessary preprocessing steps and evaluation metrics is intended to alleviate development efforts and facilitate the comparison of results across different studies. The toolbox is available at: this https URL.
Abstract (translated)
高质量数据集的可用性对于自动驾驶车辆中行为预测算法的开发至关重要。本文强调了在运动预测研究中标准化使用某些数据集的必要性，以简化比较分析，并提出了一系列工具和做法来实现这一目标。我们综合了广泛的经验和对当前文献的全面回顾，以提供一个为研究轨迹预测问题而设计的开源工具箱。明确的数据预处理步骤和评估指标的定义旨在减轻开发负担，并促进不同研究之间的结果比较。该工具箱可在以下链接访问：https://this URL。
URL
https://arxiv.org/abs/2405.00604
