出租车运营模式与运力规模优化研究

发布时间：2018-01-02 03:36

本文关键词：出租车运营模式与运力规模优化研究　出处：《兰州交通大学》2016年硕士论文　论文类型：学位论文

【摘要】：近年来,国内出租车交通得到快速发展,已经覆盖所有城市及较发达乡镇,成为群众出行的重要交通方式。2008年大部门体制改革之后,运输部门从政策、标准等不同方面着手,出台了多项出租车相关的规章制度,加强对出租车行业的监管,以期提高大众的满意度,促进行业的有序发展。但在出租车发展历程中因发展思路不一致、政策措施不明确,导致出租车行业存在一些突出的问题,制约着整个行业的有序发展。其中出租车以怎样的运营模式经营、投放多大的运力规模都对行业的有序发展有着很大的影响。因此有必要对出租车的运营管理模式和运力规模的投放进行分析,寻找规律,探索方向,形成适合我国国情的出租车管理思路。首先,文中对出租车的服务特性做了详细的描述,并分析了其在城市运输中所发挥的职能,从而确立出租车行业未来的发展方向,并在分析出租车市场上表现出来的各种不合理现象的基础上,找到阻碍出租车交通有序发展的原因。其次,由于运营模式的选取,关系到整个出租车行业的发展方向,影响着出租车的服务质量和政府的管理效率,同时也涉及公司和司机之间的切身利益,因此,文中探讨了我国现有的几种出租车运营模式,在分析其影响因素的基础上,从不同利益方的立场出发对各种运营模式的优劣做出比较,并选取适当的评价指标(管理要求、产权关系、单车运营成本、事故承担能力和乘客满意度等),构建不同运营模式应用于特定都市条件下的优劣程度评定模型,为运输部门选取合理有效的模式提供理论依据。再次,在现阶段我国的国情条件下,人口密度很大、道路资源紧缺、环境承载力较弱,运力规模的投放必须由运管部门进行干预。因此,文中将制约出租车运力规模的各个因素进行综合考虑,从中挖掘出起决定作用的因子,了解其对运力规模的影响机理,并在考虑不同预测方法优劣度的基础上,以因子分析法的原理结合BP神经网络理论,构建出租车运力规模预测模型。最后,以兰州市为分析对象,在考虑因素可量化和数据易收集的基础上,确定适当数目的影响因素并从相关部门收集数据,用因子分析法对关联性较大的各因素进行统计分析,重新生成数量较少且无关联性的因子,将其作为BP神经网络的输入,训练网络并对其性能进行测试,并用其预测兰州市规划年内合理的出租车运力规模。
[Abstract]:In recent years, the domestic taxi traffic has developed rapidly, has covered all cities and more developed towns, and has become an important mode of transportation for the masses. In 2008, after the reform of the large sector system, the transport sector started from the policy. Standards and other aspects of different aspects of the introduction of a number of taxi related rules and regulations to strengthen the taxi industry supervision in order to improve public satisfaction. Promote the orderly development of the industry, but in the course of taxi development due to inconsistent development ideas, policies and measures are not clear, leading to some outstanding problems in the taxi industry. It restricts the orderly development of the whole industry. Among them, what kind of operation mode does the taxi operate. Therefore, it is necessary to analyze the operation management mode and capacity scale of taxi, to find out the law and explore the direction. First of all, the paper describes the characteristics of taxi service in detail, and analyzes its functions in urban transportation. In order to establish the future direction of development of the taxi industry, and on the basis of analyzing the various unreasonable phenomena in the taxi market, find out the reasons that hinder the orderly development of taxi traffic. Secondly. Because of the choice of operation mode, related to the development direction of the whole taxi industry, affecting the taxi service quality and government management efficiency, but also involving the immediate interests of the company and drivers, so. Based on the analysis of the influencing factors, this paper compares the advantages and disadvantages of various taxi operation modes from the standpoint of different stakeholders. And select appropriate evaluation indicators (management requirements, property relations, bicycle operating costs, accident bearing capacity and passenger satisfaction, etc.). Construction of different operational models applied to specific urban conditions of the evaluation model of the pros and cons for the transport sector to select a reasonable and effective model to provide a theoretical basis. Thirdly, in the current situation of our national conditions. The population density is very large, the road resources are scarce, the environmental carrying capacity is weak, the transportation capacity scale must be intervened by the transportation management department. Therefore, the paper will restrict the taxi capacity scale each factor to carry on the comprehensive consideration. The factors that play a decisive role are excavated, and the influence mechanism of the factors on the capacity scale is understood. On the basis of considering the advantages and disadvantages of different forecasting methods, the principle of factor analysis is combined with the BP neural network theory. Finally, taking Lanzhou City as an analysis object, on the basis of quantifiable factors and easy data collection, determine the appropriate number of factors and collect data from relevant departments. The factor analysis method is used to analyze the factors with high correlation. The factors with less and no correlation are regenerated and used as the input of BP neural network to train the network and test its performance. It predicts the reasonable scale of taxi capacity in the planning year of Lanzhou City.
【学位授予单位】：兰州交通大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：F572

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