High-precision vehicle trajectory data from an intersection in Shanghai: A unique dataset for microscopic traffic flow studies collected by drone and GNSS receiver

IF 1 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2024-08-29 DOI:10.1016/j.dib.2024.110864
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Abstract

Vehicle trajectory data are invaluable for driving behaviour and traffic flow modelling studies, especially at the microscopic level. However, existing public vehicle trajectory datasets only provide data with inherent errors and lack the corresponding ground truth. This study presents a comprehensive vehicle trajectory dataset obtained using both drone and high-precision Global Navigation Satellite System (GNSS) receiver technologies with an error of less than 5 cm. The dataset contains 70 complete trajectories with a total of 10,840 data points and an average length of 48.4 m. This includes 27 left-turn trajectories, 27 through trajectories and 16 right-turn trajectories. The trajectories collected by the centimetre-level precision GNSS receiver can be regarded as the ground truth of the trajectories extracted by the drone video. Researchers can use these two trajectory datasets to analyse driving behaviour at interactive scenarios, validate and calibrate microscopic traffic flow models, and validate trajectory reconstruction methods.

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上海十字路口的高精度车辆轨迹数据:利用无人机和全球导航卫星系统接收器收集的用于微观交通流研究的独特数据集
车辆轨迹数据对于驾驶行为和交通流建模研究非常宝贵,尤其是在微观层面。然而,现有的公共车辆轨迹数据集只能提供存在固有误差的数据,缺乏相应的地面实况。本研究介绍了利用无人机和高精度全球导航卫星系统(GNSS)接收器技术获得的综合车辆轨迹数据集,其误差小于 5 厘米。该数据集包含 70 个完整轨迹,共有 10,840 个数据点,平均长度为 48.4 米,其中包括 27 个左转轨迹、27 个通过轨迹和 16 个右转轨迹。厘米级精度的全球导航卫星系统接收器收集的轨迹可视为无人机视频提取的轨迹的地面实况。研究人员可以利用这两个轨迹数据集分析交互场景下的驾驶行为,验证和校准微观交通流模型,并验证轨迹重建方法。
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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