Traffic Route Dynamic Guidance Based on Coupling of Time Recursive and Artificial Neuron Network

Abstract

The relationship of road conditions and time change on the basis of people-machine-environmental coupling is researched. A prediction method of time recursive to confirm the shortest time of route is proposed. This method is as an accumulated experience basing on the idea of supervised learning in artificial neural network, colligating with the difference of road conditions during different time section, the human factors function, and the randomness of the accident in course of driving, thus the guidance of the traffic route is realized. Comparing with the real-time road conditions and accumulated experience, the method of time guidance prediction could offer real-time and effective road information for drivers. This guidance technology assists drivers to judge correctly in time and reduces the time losses because of the lack of the experience and the accidents. The guidance technology can be applied to the vehicles, which are with GPS. The example indicates that the model is effective combined with the real data.