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Trajectory prediction of vehicles turning at intersections using deep neural networks
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Trajectory prediction of vehicles turning at intersections using deep neural networks
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Trajectory prediction of vehicles turning at intersections using deep neural networks
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Journal Article
Trajectory prediction of vehicles turning at intersections using deep neural networks
2019
Overview
In this paper, an early prediction of vehicle trajectories and turning movements are investigated using traffic cameras. A vision-based tracking system is developed to monitor intersection videos and collect vehicle trajectories with their labels known as turning movements. Firstly, two intersection videos are monitored for 2 h, and collected trajectories with their labels are used to train deep neural networks and obtain the turning models for the prediction task. Deep neural networks are further investigated on a third intersection with different video settings. The future 2 s evaluation of trajectories shows the success of long short-term memory networks to early predict the turning movements with more than 92% accuracy.
Publisher
Springer Berlin Heidelberg,Springer Nature B.V
