Dragon Lake Parking Dataset

The Dragon Lake Parking (DLP) Dataset contains annotated video and data of vehicles, cyclists, and pedestrians inside a parking lot. We collected it by flying a drone above a huge parking lot. Abundant vehicle parking maneuvers and interactions are recorded. To the best of our knowledge, this is the first and largest public dataset designated for the parking scenario (up to April 2022), featuring high data accuracy and a rich variety of realistic human driving behavior. The potential applications of this dataset include but are not limited to trajectory prediction, trajectory analysis, traffic analysis, behavior analysis, behavior cloning, and imitation learning.龙湖停车场（Dragon Lake Parking, DLP）数据集包含停车场内车辆、骑行者与行人的标注视频及相关数据。本数据集通过在大型停车场上空搭载无人机采集所得，记录了丰富的车辆泊车动作与交互场景。据我们所知，截至2022年4月，本数据集是首个且规模最大的专为停车场场景设计的公开数据集，兼具数据精度高、真实人类驾驶行为类型丰富两大优势。本数据集的潜在应用场景包括但不限于轨迹预测（trajectory prediction）、轨迹分析（trajectory analysis）、交通分析（traffic analysis）、行为分析（behavior analysis）、行为克隆（behavior cloning）与模仿学习（imitation learning）。

搜集汇总

背景与挑战

背景概述

Dragon Lake Parking Dataset是一个由加州大学伯克利分校发布的停车场场景数据集，包含通过无人机采集的车辆、行人和骑行者的注释视频与轨迹数据。该数据集规模庞大，拥有30个场景、超过31万帧和5千多个代理，是截至2022年4月首个且最大的公共停车场数据集，具有高精度和多样化的真实驾驶行为，适用于轨迹预测、交通分析等研究。