Research on Application of Two-degree Fuzzy Neural Network in ATO of High Speed Train

As the important equipment to take the train driver's place and realize railway transportation automation,the automatic train operation(ATO) system draws extensive attention among domestic and overseas scientific and technical workers.ATO performance concerns safety and productivity of railway transport systems.A good high-speed train control method can satisfy people's demands for safety,punctuality,comfort and fast convenience of high speed railways.On the basis of preceding research and the fact that fuzzy neural networks have the characteristics of abstracting experience and implementing deduction,two-degree fuzzy neural networks are used to control high speed train running processes.The first sub-network simulates on excellent train driver's operation to obtain the optimal train running conditions with reference to the train travelling speed,railway line conditions,train formation,train timetable,distance to the object point and corresponding permissible speed at the present time.The next sub-network is used to deduce the train running speed from the obtained train running conditions and the present railway traffic conditions,such as the railway line conditions,train location on the line,train formation,train timetable,distance to the object point and permissible velocity at the object point on the track.Simulation results show that the solution to the high speed train control is correct and effective as anticipated.