@article{ref1,
title="A red-light running prevention system based on artificial neural network and vehicle trajectory data",
journal="Computational intelligence and neuroscience",
year="2014",
author="Li, Pengfei and Li, Yan and Guo, Xiucheng",
volume="2014",
number="",
pages="892132-892132",
abstract="The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs) to approximate the complex driver behaviors during yellow and all-red clearance and serve as the basis of an innovative red-light running prevention system. The artificial neural network and vehicle trajectory are applied to identify the potential red-light runners. The ANN training time was also acceptable and its predicting accurate rate was over 80%. Lastly, a prototype red-light running prevention system with the trained ANN model was described. This new system can be directly retrofitted into the existing traffic signal systems.<p /> <p>Language: en</p>",
language="en",
issn="1687-5265",
doi="10.1155/2014/892132",
url="http://dx.doi.org/10.1155/2014/892132"
}