Optimization Design And Simulation Of ATO Control Strategy For Urban Rail Transit Based On Multi-objective

With the rapid development of cities in China,the scale of cities and population have been increasing,which result in increased pressure on urban traffic.In order to solve this problem,rail transit system which is the main force of the urban traffic needs to be improved with operational efficiency and be insured the level of relevant performance indicators.How to ensure safe,fast and smooth automatic operation of trains has become a significant issue in research.The Automatic Train Operation(ATO)system is the core part of Automatic Train Control(ATC)system,and its control strategy has become the key of issue.The control strategy during the train operation directly affects the performance indicators such as safety,punctuality,parking accuracy,and energy saving of the train operation,and passenger comfort.Good control strategy has critical significance to train operation.Therefore,it is very necessary to study the ATO control strategy.In this thesis,the control strategy of ATO system for urban rail transit is optimized and simulated.The main research contents are as follows:(1)It was solved that the performance indicators were not considered comprehensively in the current research on ATO control strategy in the thesis.The various force conditions of the train in the operation process and the actual requirements of various actual performance indicators were considered based on reviewing and analyzing the relevant theories and technologies.Taking train energy consumption,parking accuracy and punctuality as the objectives,a multi-objective optimization model for ATO was constructed by combining with ATO control characteristics and multi-objective optimization theory.(2)The train operation simulation was carried out based on the train operation characteristics under the mixed strategy,and the corresponding train performance indicators were calculated,which provided data for the subsequent algorithm solution.(3)Through the analysis and comparison of various algorithms,the non-dominated sorting genetic algorithm ?(NSGA-?)based on Pareto optimal solution was selected to solve the ATO multi-objective optimization model and the corresponding Pareto solution set was obtained.In order to obtain the tracking curve of the train,the corresponding optimization target curve was generated according to the train running schedule after completing the solution.Finally,the efficiency of the algorithm was verified by comparing with the results of relevant literature.(4)In order to control the train to track the target curve accurately and achieve the ideal control effect,the characteristics of ATO control and advantages of various algorithms were analyzed in this thesis.Then,the ATO controller based on the integrated intelligent control algorithm was designed.(5)Through the above research,the design of the optimal control strategy of ATO was completed.In order to vertify the efficiency of control strategy,the simulation platform of ATO optimization control strategy was built.Then,it was simulated by taking Beijing Subway Line 8 as an example,and result data of simulation was compared with the actual train operation data.The results show that the ATO optimization control strategy designed in this thesis has a good control effect on train operation,and achieves efficient control of the train.Meanwhile,the various performance indicators are also optimized.