Citation

Li P, Li Y, Guo X. Comput. Intell. Neurosci. 2014; 2014: 892132.

Affiliation

Transportation School, Southeast University, 2 Sipailou, Nanjing 210096, China.

Copyright

(Copyright © 2014, Hindawi Publishing)

DOI

10.1155/2014/892132

PMID

25435870

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.

Language: en