Determination of Easy Parking Points of Train Driving Interval Based on UAS and BP Neural Network Linear Grey system

Abstract

As Chinese railway network continues to expand from the eastern area to the western area, the accidents of trains forced parking caused by traction network failure occur in the course of operation from time to time, which not only seriously affects the economic and social development of China, but also poses a serious threat to the safety of passengers ' lives and property. When train power is lost, it will passively stop for waiting for rescuing or use the self-stored energy to carry out for self-rescue to the nearest station. For this reason, a grey linear regression model based on BP Neural network is proposed to determine easy parking points of train running interval with UAS simulation platform, and compared with UAS simulation results, it is proved that the BP neural network grey system can complete the determination of easy parking points of train running interval well.