Trajectory Prediction of Vehicles Turning at Intersections using Deep Neural Networks

Document Type

Article

Publication Date

6-28-2019

Publication Title

Machine Vision and Applications

First page number:

1

Last page number:

13

Abstract

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.

Keywords

Vehicle trajectories; Traffic cameras; Vision-based tracking system; Trajectory prediction; Long short-term memory networks

Disciplines

Artificial Intelligence and Robotics | Transportation Engineering

Language

English

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