作者
Xiaowei Shi, Dongfang Zhao, Handong Yao, Xiaopeng Li, David K Hale, Amir Ghiasi
发表日期
2021/12/1
期刊
Communications in transportation research
卷号
1
页码范围
100014
出版商
Elsevier
简介
High-granularity vehicle trajectory data can help researchers develop traffic simulation models, understand traffic flow characteristics, and thus propose insightful strategies for road traffic management. This paper proposes a novel vehicle trajectory extraction method that can extract high-granularity vehicle trajectories from aerial videos. The proposed method includes video calibration, vehicle detection and tracking, lane marking identification, and vehicle motion characteristics calculation. In particular, the authors propose a Monte-Carlo-based lane marking identification approach to identify each vehicle's lane. This is a challenging problem for vehicle trajectory extraction, especially when the aerial videos are taken from a high altitude. The authors applied the proposed method to extract vehicle trajectories from several high-resolution aerial videos recorded from helicopters. The extracted dataset is named by the …
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