2023 IEEE Vehicle Trajectory Dataset Fusion Contest

Submission Dates:
11/29/2022 to 11/30/2024
Citation Author(s):
Yi
HE
Bo
CAO
Ching-Yao
Chan
Submitted by:
Yi HE
Last updated:
Wed, 11/30/2022 - 10:46
DOI:
10.21227/ty7k-j136
Data Format:
Links:
License:
Creative Commons Attribution

Abstract 

The high-precision and long-distance extraction and construction of vehicle trajectory data and microscopic traffic flow characteristics are critical for traffic safety studies. Current research typically relies on a limited number of datasets which suffer from vehicle detection inaccuracy and limitation of the coverage area. Therefore, we establish a high-precision and long-distance vehicle trajectory dataset of urban scenarios. Primary features of the established dataset: (1) the trajectory data are extracted based on a trajectory extraction framework that contains the video stabilization, vehicle detection, vehicle tracking, data repair and smoothing. (2) The broken trajectory data caused by occlusion are connected through fusing tracking results at different frame rates based on the Kalman filter and Hungarian Algorithm. (2) Long-distance trajectory data from multi-videos are constructed based on video stitching, video fusion and trajectory fusion. This trajectory dataset can provide the high-precision and long-distance vehicle trajectory data for those data-driven studies in transportation. We hope this dataset can support the more transportation researches.

Instructions: 

The dataset can be used to support the transportation researches.

Competition Dataset Files

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    Documentation

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