| Urban rail transport has seen unprecedented rapid development in the last decade.Compared to conventional public transport systems on the ground,it does not take up road space,has no risk of congestion,operates at a high speed and has a high energy consumption ratio.The preparation of train timetable plays a top-down role in the management process of urban rail transit operation to undertake the pre-planning and post-arrangement.The scientific and effective development of train timetable has a positive effect on improving the quality of service and reducing the energy costs of the urban rail operator of the entire urban rail network.This thesis combines mathematical planning with weighted closeness centrality to propose a new passenger-oriented schedule optimization model for the whole network based on complex network theory.The model takes into account the practical data of passengers inbound and outbound,network passenger flow distribution,passenger travel time and energy cost,so as to minimize the average travel time of passengers and improve the service quality for passengers of the whole transit network.The effectiveness of the proposed method was verified by taking Shanghai urban rail network as an example,and the correlation between passenger flow(socioeconomic),energy consumption-time relationship of intervals(physical),edge betweenness centrality(network topology)and time change was analyzed.The results show that the change of interval travel time relative to minimum time was negatively correlated with passenger flow,slope of fitted energy consumption-time curve and edge betweenness centrality.Finally,a sensitivity analysis was implemented for intervals and lines to identify the intervals and lines with the greatest impact on network efficiency,which provides a reference basis for timetable preparation.The main work of this study are shown as follows:(1)Discriminate complex network types and network modeling methods:In this thesis,the network type of Shanghai urban rail transit is determined based on the statistical characteristics of the network such as degree,characteristic path length,clustering coefficient,and betweenness centrality,etc.;the topological model of Shanghai urban rail transit network is constructed by using the Space-L method according to the characteristics of the research target.(2)Solve the distribution of passenger flow over the entire transit network: The factors that affecting passenger path assessments are analyzed according to the individual characteristic,operation organization and behavioral characteristics,and the passenger travel time network and passenger travel path generalized cost model are constructed.In the network traffic distribution model,the conventional Dijkstra algorithm for solving shortest path is improved,and the method of successive averages(MSA)is applied to compute the model to obtain the passenger flow for each interval in the network.(3)Explore the relationship between interval energy consumption and travel time(E-T):According to the train dynamics model and motion model,the optimization model of minimum energy consumption target speed curve of train based on MILP is constructed and the energy consumption-timerelationship of the intervals is determined.(4)Construct the network-wide timetable optimization model: A network-wide timetable model is constructed based on the passenger flow distribution results,with the average travel time as the target,considering energy consumption constraint,interval time constraint and line time constraint.(5)Analyze the correlation and sensitivity of interval and line time:Taking the Shanghai urban rail network as a case study,the effectiveness of the network-wide timetable optimisation model based on complex network theory proposed in this thesis is verified,and Spearman correlation analysis and sensitivity analysis of intervals and line times are carried out on the optimization results. |
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