Study On The Model Algorithm And Simulation Platform Of Conflict Detection And Real-time Scheduling For High-speed Railway Train Operations

The high-speed railway with high transport speed and punctuality rate has become the main way of people's daily travelling,which greatly increases the capacity of passenger transportation.Compared with the general-speed railway transportation,the high-speed railway has a higher design and operation standards,thus brings higher requirements to the centralized traffic control system and train operation control system.In China's large-scale and complex railway network system,train operation is often disturbed by various complicated conditions,and deviates from the scheduled timetables.If there is no timely adjustment to the train operation plan,the transportation efficiency will be decreased,and even,the operation safety will be endangered.Therefore,the centralized traffic control system and train operation control system need to detect potential conflicts in time and generate scheduling strategies.This paper mainly explores the conflict detection and optimization scheduling strategies of high-speed train operations.The research contents and conclusions are as follows:(1)The causes of high-speed train operation conflicts and its classifications are analyzed and summarized.Setting several most common types of conflicts as research objects,the decision rules and corresponding resolution methods of conflicts are discussed.Based on the application of cellular automata in the field of traffic flow simulation and prediction,the cellular automata model of high-speed train operation under moving-block system is proposed,based on which,the conflict detection module has been added to this model.(2)Based on the theory of predictive control,a conflict detection and scheduling optimization framework of train operations is proposed.Through the rolling prediction,the timeliness and accuracy of the collision detection is improved.By calibrating the model with the actual operation information of the train,the match degree between the model and the real train movements can be improved,and thus,the robustness of the scheduling strategy can be increased.(3)The branch-and-bound algorithm is utilized to generate scheduling strategies of high-speed trains under the moving-block mode,and the branching and pruning rules as well as the selection of the bounding functions are analyzed in detail.At the same time,the limitation of the branch-and-bound algorithm is analyzed when the scale of the solution space is very large,and the idea is established about combining the exact branch-and-bound algorithm with the heuristic one.(4)Based on the Visual Studio 2015 platform,the high-speed railway train operation and scheduling simulation platform under the environment of moving-block mode is implemented using C++ language in the MFC environment.Combined with the real network of high-speed railway in China,the experiment simulation scene is created.The simulation results testify the feasibility and rationality of the developed train operation simulation model,and the high-speed train operation conflict detection and scheduling optimization framework based on predictive control.Moreover,compared with the first-come-first-service(FCFS)algorithm,the efficiency and superiority are proved of the branch-and-bound algorithm at finding the optimal scheduling strategies.