Research On Train Operation Regulation Of Urban Rail Transit

In the actual passenger transport of urban rail transit, train delays happen frequently due to the impact of external factors. It may lead to the phenomenon which trains deviate from the scheduled time if the delay can not be adjusted in time. Advanced CBTC technology is widely used in urban rail traffic which not only can shorten the train tracking interval but also improve the transportation efficiency. Then the impact from delay spread on operation diagram becomes more obvious. In severe cases it even may disturb the normal order of entire operation diagram. Therefore the regulation for train delays is significant.Objective optimization which proposed in many literatures often ignore the important factors of passenger flow and the intelligent algorithms that solve the model also exist some shortcomings. Based on above analysis, the improved models and algorithms to increase the accuracy of results and real time operation by combining the practical passenger traffic. Finally, the IPSO algorithm is determined to solve train regulation at the same time the feasibility of proposed model and algorithm can be verified according to the results of simulation testsIn this thesis, the work is as follows:For the characterized of pure passenger transport, it should consider the influence of passenger flow on stop time. After using regression analysis to curve fitting the scatter plot that consist of average passenger traffic and stop time, it can get the regression model of stop time. Then the stop time model is added in the optimization objectives and constraints to improve. At the same time by drawing on the railway operation diagram dynamic performance and index evaluation system, several indexes for urban rail traffic delayed regulation are proposed which provides the basis for quantitatively measuring the results.Firstly on the basis of PSO, inertia weight and speed are improved and analyzed in the part of solving model. Then according to the characteristics of train operation regulation, the algorithm processes are determined. The results for simulation experiments which based on GA, PSO and IPSO show the better feasibility when the optimization model improved algorithm that proposed by this thesis are used for solving the train operation regulation.In summary, this thesis takes Chengdu Metro actual operating data as the basis to build the objective function and IPSO algorithm which consider the impact of passenger flow. The simulation results demonstrate its feasibility.