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.
journal_name
Comput Intell Neuroscijournal_title
Computational intelligence and neuroscienceauthors
Li P,Li Y,Guo Xdoi
10.1155/2014/892132subject
Has Abstractpub_date
2014-01-01 00:00:00pages
892132eissn
1687-5265issn
1687-5273journal_volume
2014pub_type
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