通化市停车需求预测研究

发布时间：2018-10-19 19:38

【摘要】：城市静态交通的主要任务就是解决停车难的问题,通过城市停车规划,合理引导停车需求。城市停车需求预测是对城市未来停车规模的预测,通过考虑城市用地、道路交通等因素的影响,对城市停车现状进行分析,掌握其内在的发展规律,并综合运用科学的方法合理预测未来停车规模,力求未来停车需求规模合理、均匀分布、结构合理,使停车设施建设规模既能满足当下城市停车需求,又为未来停车设施建设提供充足的空间。实现城市停车需求预测科学、合理,具有深远的意义。本文以城市停车需求为研究对象,按照问题提出、理论分析、停车调查、模型构建和模型应用的思路,首先对我国城市停车中出现的问题进行分析,通过分析国内外学者的研究成果以及发展趋势,本文在顺应目前发展趋势的基础上,综合考虑研究区域的实际,确定论文的主要研究内容及研究的技术路线。通过理论分析,对城市停车设施和城市停车需求进行分析界定。分别从宏观和微观角度分析影响停车需求的因素,为后面模型参数选取和模型构建提供依据。确定停车调查内容及实施方案,并针对停车设施供给调查和停车特征调查分别设计调查方法及调查表;对选取的特性指标停车周转率、泊位利用率、高峰停放指数进行界定和分析。通过对国内外常用的停车需求预测模型进行分析和对比,根据停车需求的分类及特性,分别构建城市基本停车需求预测模型和城市社会停车需求预测模型,并给出各个预测模型的参数取值方法。以吉林省通化市停车需求预测为例,通过对通化市停车调查,对停车供给总体情况、停车片区分布以及停车利用特性指标进行分析,掌握通化市停车发展特点以及模型参数取值,从而利用停车预测模型对基本停车需求和社会停车需求进行预测,对停车调查实施方案和停车需求预测模型的适用性进行实际论证。应用过程中,根据遇到的问题进一步调整、优化模型,以使模型更加合理。
[Abstract]:The main task of urban static traffic is to solve the problem of parking difficulty and reasonably guide parking demand through urban parking planning. The forecast of urban parking demand is the prediction of the future parking scale of the city. By considering the influence of urban land use, road traffic and other factors, the present situation of urban parking is analyzed, and the inherent development law is mastered. The scale of parking demand is reasonable, even distribution and structure is reasonable, so that the scale of parking facilities can meet the current parking demand. It also provides sufficient space for the construction of parking facilities in the future. The realization of urban parking demand prediction is scientific, reasonable and has far-reaching significance. This article takes the urban parking demand as the research object, puts forward according to the question, the theory analysis, the parking survey, the model construction and the model application train of thought, first carries on the analysis to our country city parking question which appears in the city parking. By analyzing the research results and development trends of domestic and foreign scholars, this paper, on the basis of conforming to the current development trend, synthetically considers the reality of the research area, and determines the main research contents and the technical route of the research. Through theoretical analysis, the urban parking facilities and parking requirements are analyzed and defined. The factors affecting parking demand are analyzed from macro and micro angles respectively, which provide the basis for model parameter selection and model construction. To determine the content and implementation plan of parking survey, and to design investigation methods and questionnaires for parking facilities supply survey and parking characteristic survey, and to select characteristic indicators, parking turnover rate, berth utilization ratio, parking facilities, parking facilities and parking facilities. Peak parking index is defined and analyzed. Based on the analysis and comparison of the commonly used parking demand forecasting models at home and abroad, according to the classification and characteristics of parking demand, the basic parking demand forecasting model and the urban social parking demand forecasting model are constructed respectively. The parameter selection method of each prediction model is also given. Taking the forecast of parking demand in Tonghua City of Jilin Province as an example, through the investigation of parking in Tonghua City, the general situation of parking supply, the distribution of parking area and the characteristic index of parking utilization are analyzed. In order to predict the basic parking demand and the social parking demand, we can master the characteristics of the parking development in Tonghua City and select the parameters of the model, so as to forecast the basic parking demand and the social parking demand. The application scheme of parking survey and the applicability of parking demand prediction model are demonstrated. In the process of application, the model is further adjusted according to the problems encountered and the model is optimized to make the model more reasonable.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U491.7

【相似文献】