CTCS-3 Train Control System Modeling And Simulation Of The Downgrading Scenarios

The of the Chinese train control system(CTCS) is the independent research and development system of our country and it is the important technical guarantee for the train to keep the running safety and improve the running efficiency. CTCS-3 train operating control system is a reference to the relevant technologies in Europe, and it makes railway wireless network and ZPW2000 to form together in accordance with the present situation of Chinese railway system, which can not learn from the previous case. It is valuable to study the train control system in different conditions, especially the recovery of the equipment faults in the train operating control system for research on the security issues of the system.The main task of improving train control system is to ensure the safety of the train running. In the thesis, some kinds of downgrade scenarios are described in detail for CTCS-3, and the different ones are modeled and analyzed, focusing on analysis of the probability changes of each state and the transforming relationships among different states in train control system.The normal level transformation of train control system is analyzed by using stochastic Petri net, and the model and simulation of the scenario are set up. Meanwhile, the scenario of the level transformation brought by equipment faults is also simulated and analyzed to ensure improving the security of CTCS.The detailed simulation is done for the faults of the balises caused by the code element error, transmission delay, transmission failure, and the simulation of the faults of on-board equipment is also operated brought by transmission error, handoff, lost connection. The another task is to simulate and model the connection progress of GSM-R wireless network from downgrading to upgrading. Finally, the TimeNet4.0 analysis platform is used to validate the correctness of the model, and find out the curve of probability distribution, do researching of the CTCS-3 operation in downgrade scenarios quantitatively and qualitatively.