A Red-Light Running Prevention System Based on Artificial Neural Network and Vehicle Trajectory Data

الملخص EN

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.