| As the traffic aorta of a modern metropolis,urban rail transit is characterized by speed,convenience,comfort and safety,etc.The construction of urban rail transit plays a great role in alleviating the road traffic congestion in the modern cities.For the operation and management of urban rail transit,train schedule is the core of its operation and management,but with the speeding up of urbanization,with the acceleration of urban rail transit network construction,the passenger flow demand of urban rail transit is also increasing,the traditional fixed departure interval period of time has been more and more difficult to adapt to the large-scale passenger train schedules.Therefore,in the case of increasing passenger flow,optimizing the train departure frequency and arrival and departure time based on dynamic passenger flow demand and limiting the full load rate range so as to make the train schedule match with dynamic passenger flow demand can reduce the passenger waiting time,improve the passenger comfort and thus improve the service level.Considering the service level of train schedules not only reduce the passenger travel time,improve the satisfaction degree of the passengers,reduce the operating safety,because of the crowded at the same time also can improve the efficiency of enterprise operation and management of urban rail transit,reduce business operating costs,improve the urban rail transit,the share rate of both passengers and for urban rail transit operation enterprise,more in line with the schedule of dynamic traffic demand has obvious advantages.Based on the analysis of passenger flow characteristics and demand characteristics of urban rail transit,this paper proposes an optimization model of urban rail transit schedule considering the service level according to the service level index of urban rail transit.In a single road and under the operation scheme of two different size/road,on the basis of dynamic traffic data to build urban rail transit schedule optimization model,by using MATLAB genetic algorithm to solve at the same time,the final in Beijing metro line 4-daxing lines of actual data to verify the validity of the model,the main completed the following work:(1)Firstly,the paper analyzes the passenger flow of urban rail transit,introduces the spatial and temporal distribution characteristics of the passenger flow,analyzes the characteristics of passenger flow demand of urban rail transit and introduces the service level index of urban rail transit lines,so as to establish the theoretical basis for the next step of schedule optimization model.(2)Based on the dynamic passenger flow data of urban rail transit,the schedule optimization model of urban rail transit with service level in consideration of two different operation organization forms,namely single route and large route,is proposed respectively.Model the minimum passenger waiting time as the optimization goal,delimits the scope of train load factors,considering the train operation and train the ability of periodic constraint in constraints,respectively under two kinds of operation organization form is optimized,and designs genetic algorithm to solve the model,it is concluded that the level of both passengers waiting time and car filled train schedules.(3)Take Beijing Metro Line 4-Daxing line as the research object,analyze the passenger flow distribution law and schedule status of the line,and substitute the actual operation situation of the line in the evening rush hour on weekdays into the model for calculation,and obtain the optimized train schedule under the two operational organization forms respectively.(4)Compare and analyze the train schedule before and after optimization to verify the effectiveness of the model and algorithm. |
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