Research On Operational Optimization Method Of Regular Bus At Urban Rail Transit Station

With the acceleration of urbanization and the increase in the number of cars,the shortage of traffic resources and road traffic congestion have become increasingly severe.Although the proposal and implementation of the strategy “Public Transport Priorit” has increased the attractiveness of public transport to a certain extent and appropriately alleviated traffic congestion,there are still some phenomera that different modes of public transport operate independently and transfers between different modes of public transport are uncoordinated.Based on the existing layout of rail transit and regular bus network,it introduces the concept of passenger perception from the perspective of operational optimization,fully considers the transfer organization coordination condition between rail transit and regular bus,optimizes the timeatable,platform environment and transfer indication sign of regular bus at urban rail transit station,and further promotes the transfer connection between rail transit and regular bus,increases the attractiveness of public transport and improves the passenger’s travel perceived satisfaction.Firstly,Analyze the characteristics of regular bus at rail transit station,clarify the concepts related to operational optimization.Summarize the common connection methods of urban rail transit stations and their characteristics,sort out the common classification methods of rail transit stations,and make it clear that the research object is the first and last station or transfer station of rail transit where the surrounding land use is mainly residential and commercial.And it analyzes the transfer characteristics and passenger flow characteristics of regular bus at rail transit station,determines the connotation and content of operational optimization,then develop an operational optimization process.Secondly,study the passenger transfer process of rail transit transfer to regular bus.The transfer process is divided into the transfer walking process and the platform waiting process,the influencing factors in these processes are explored,the fitting method of the tranfer walking process is proposed,the platform waiting time calculation method of non-transfer passengers and transfer passengers is given.Then the transfer organization coordination conditions are analyzed from the objective and perception levels,the operational optimization content of time coordination and space coordination is pointed out at the objective level,and the concept and calculation method of the perception platforms waiting time cost are proposed at the perceptual level.Then,establish two operational optimization models from the objective and perceptual level and design a genetic algorithm based on the idea of greedy algorithm to solute models.Put forward model assumptions,establish an operational optimization model not consider the passenger perception that takes the minimum platform waiting time of the passenger as the objective function and an operational optimization model considering the passenger perception with the minimum perception platform waiting time cost of the total passenger as the objective function,and explore the model constraints.The optimal running timetable of regular bus is solved,and the genetic algorithm is designed to solve the model by combining the local optimal solution idea of greedy algorithm.Finally,use the D6 regular bus case around Nanjing Youfangqiao Metro Station to verify the two operational optimization models,and apply the operational optimization method.Investigate the operational optimization status of this case,identify existing problems,collect the data of the operational optimization case and use MATLAB software programming,use the designed GA to solve the model.It is found that the operational optimization model considering passenger perception is better than the model that does not consider passenger perception.Besides,combining the results of spot investigation,questionnaire survey and model solution,operational optimization suggestions are provided.