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论文编号：	14261
作者编号：	2320190798
上传时间：	2023/12/10 22:54:07
中文题目：	基于断面客流预测的T市地铁5号线运力配置优化研究
英文题目：	Research on optimization of transport capacity allocation of Metro Line 5 in T City based on cross-section passenger flow prediction
指导老师：	李勇建
中文关键字：	城市轨道交通；客流运力匹配；行车方案优化；客流预测；线性规划
英文关键字：	Urban rail transit; Passenger flow capacity matching; Driving plan optimization; Passenger flow forecast; Linear programming
中文摘要：	近年来我国城市轨道交通行业飞速发展，以地铁、轻轨等为代表城市轨道交通当前已成为我国各大城市公共交通网络的骨干核心和市民日常的主要出行方式。但当前国内各城市的轨道交通运营单位普遍出现了入不敷出、常年亏损的现象，这严重阻碍了行业和城市公共基础建设的可持续发展。究其原因是国内城市轨道交通一般都采用较为固定的行车计划，这导致运力与在时空分布上具有不均衡性的客流的匹配程度较低，运能浪费严重，从而造成运营成本长期以来居高不下的问题。为了解决此问题，首当其冲的就是要降低运营成本，提升运营效益，因此如何根据客流数据精准地匹配线路运输能力，成为提升城市轨道交通运输效率和降低运营成本的重要研究问题。 本文针对当前城市轨道交通客流与行车计划不相匹配的问题，以T市地铁5号线为研究对象，从城市轨道交通客流数据的分布特征出发，利用统计学方法，系统分析线路的历史客流数据，得出其时空分布特征；再结合5号线现行的行车计划，分析得出客流需求与运力配置目前存在的冲突和问题；然后以地铁5号线断面客流历史数据为样本，利用SPSS数据处理软件，根据最大断面客流数据内在的变化规律，分别用线性回归、时间序列算法构建得出客流的预测模型，通过参数估计、假设检验对比选取拟合程度最好的模型进行最大断面客流预测。在此基础上运用线性规划算法，以实现线路运营成本最小化为目标，综合考虑断面满载率、乘客候车等待时间、车辆资源及线路能力等制约城市轨道交通运营运力提升的条件，构建了客流与运力精确匹配的优化模型，并最终求得在满足客流和运营需求条件下使得运营成本最低的列车运行计划，最后通过对比5号线既有行车方案提出行车运营管理的提升建议。 本次研究从客流数据分析、到最大断面客流预测，再到基于预测客流制定相匹配的列车运行计划，为优化提升城市轨道交通客流与运力之间的匹配关系实现运营成本最小化提供了可行方案，这种适应客流变化的运力配置方法能够有效解决5号线既有的客流和运力矛盾，在缓解高峰列车拥挤的同时减少平峰运力浪费，实现了节能降本、提升城市轨道交通的运营效益的运营管理目标。
英文摘要：	In recent years, China's urban rail transit industry has developed rapidly, and urban rail transit represented by subway and light rail has become the backbone of public transport network in major cities and the main daily travel mode of citizens. However, the current domestic urban rail transit operating units generally appear to be unable to make ends meet, perennial losses, which seriously hinders the sustainable development of the industry and urban public infrastructure. The reason is that the domestic urban rail transit generally adopts a relatively fixed traffic plan, which leads to a low matching degree between the transport capacity and the unbalanced passenger flow in the spatial and temporal distribution, and a serious waste of transport capacity, resulting in a long-term high operating cost. In order to solve this problem, the first thing is to reduce the operating cost and improve the operating efficiency. Therefore, how to accurately match the line transportation capacity according to the passenger flow data has become an important research issue to improve the transportation efficiency of urban rail transit and reduce the operating cost. Aiming at the problem of mismatch between current urban rail transit passenger flow and travel plan, this thesis takes T Metro Line 5 as the research object, starts from the distribution characteristics of urban rail transit passenger flow data, uses statistical methods to systematically analyze the historical passenger flow data of the line, and obtains its spatial and temporal distribution characteristics. Combined with the current traffic plan of Line 5, the conflicts and problems between passenger flow demand and transport capacity allocation are analyzed. Then, taking the historical passenger flow data of Metro Line 5 section as the sample, SPSS data processing software was used to construct the passenger flow prediction model by linear regression and time series algorithm according to the internal change rule of the passenger flow data of the maximum section, and the model with the best fitting degree was selected to predict the passenger flow of the maximum section through parameter estimation and hypothesis testing. On this basis, linear programming algorithm is applied to achieve the goal of minimizing line operating costs, and comprehensively consider the conditions restricting the improvement of urban rail transit operating capacity such as section full load rate, passenger waiting time, vehicle resources and line capacity, and build an optimization model that accurately match passenger flow and capacity. Finally, the train operation plan with the lowest operating cost under the condition of meeting the passenger flow and operation demand is obtained. Finally, the train operation management improvement suggestions are put forward by comparing the existing train operation plan of Line 5. From the analysis of passenger flow data, to the prediction of maximum section passenger flow, to the formulation of matching train operation plan based on the forecast passenger flow, this study provides a feasible scheme for optimizing and improving the matching relationship between passenger flow and capacity of urban rail transit to minimize operating costs. This capacity allocation method adapted to passenger flow changes can effectively solve the existing contradiction between passenger flow and capacity of Line 5. The operation management goal of saving energy, reducing cost and improving the operation efficiency of urban rail transit is realized by alleviating train congestion in peak hours and reducing the waste of peaking capacity.
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