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

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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Publication Details

Journal
Data in Brief
Published
2024-08-29
DOI
https://doi.org/10.1016/j.dib.2024.110864
Citations
2
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
0.41

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article

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

Jing Zhao, Ruoming Ma, Meng Wang
2 citations
Data in Brief
Autonomous Vehicle Technology and Safety
0.41
article

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

Jing Zhao, Ruoming Ma, Meng Wang
article en
2 citations

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.

Data in BriefVol. 57
University of Shanghai for Science and Technology (CN), Technische Universität Dresden (DE)
National Natural Science Foundation of China, Shanghai Shuguang Program
Openalex Percentile: Top 40%
Autonomous Vehicle Technology and Safety
0.41
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