公共交通通勤出行时间影响模型研究

发布时间：2018-05-07 06:46

本文选题：公共交通 + 多源数据　；参考：《北京工业大学》2015年硕士论文

【摘要】：通勤出行是城市居民出行的主体,随着城市的不断扩张发展,居民职住分离的现象越发明显,通勤出行时间不断延长的问题凸显出来。而公共交通作为通勤出行中服务受众最广的交通方式,其在解决居民通勤出行难题上的强大优势越来越被重视。研究居民公共交通通勤出行行为,分析通勤出行时间的影响因素及特征,对于提高居民通勤出行效率具有重要意义。首先,论文利用交通供需理论,从需求和供给两个角度,科学地梳理公共交通通勤出行时间影响因素,并根据影响因素的普遍性,从宏观和微观层面对其进行分类。确定了包括城市空间布局、经济发展水平、交通政策法规、交通出行成本、基础设施条件和企业运营水平等因素在内的影响因素集,并分析了各因素与通勤出行时间的关系。然后,论文在介绍了公交IC卡数据、轨道AFC数据、公交GPS数据、交通小区数据等多源公共交通数据结构特点的基础上,利用数据融合分析技术,提出了公共交通通勤出行时间的提取方法,具体包括多源数据关联匹配、出行链的结构提取、通勤行为判别、出行阶段起终点确定和出行时间计算五个步骤。论文详细介绍了每个步骤的处理规则,确定了相应的判断阈值,解决了地面公交上下车站点匹配等难题,实现了公共交通通勤出行时间的提取。最后,论文选取区位因素和公共交通基础条件因素,利用SPSS软件构建了通勤出行时间影响模型。根据交通小区内有无轨道交通线网,影响模型分为了两类。论文在分别对两类模型进行解释的基础上,定量分析了增加地面公交和轨道交通线网密度、促进城市多中心发展等措施,对缩短居民公共交通通勤出行时间的重要作用。结果表明,在有轨道交通的小区,地面公交线网密度每增加1km/km2,居民平均的公共交通通勤出行时间会缩短0.37分钟,而轨道交通线网每增加1km/km2,平均出行时间会缩短约1.61分钟;在无轨道交通的小区,地面公交线网密度每增加1km/km2,居民平均通勤出行时间会缩短约0.44分钟。本文的研究可为北京市公共交通线网优化和基础设施建设提供决策支持,对于改善居民通勤出行状况有重要意义。
[Abstract]:Commuter travel is the main body of urban residents' travel. With the continuous expansion and development of the city, the separation of residents and residence is becoming more and more obvious, and the problem of the continuous extension of commuter travel is highlighted. As the most widely used traffic mode in the commuter trip, public transportation is becoming more and more powerful in solving the problem of resident commuter travel. The study of commuting travel behavior and analysis of the influence factors and characteristics of commuter travel time are of great significance to improve the efficiency of commuter travel. Firstly, the thesis makes use of the theory of traffic supply and demand to scientifically comb the influence factors of public transportation commuter travel time from two perspectives and according to the shadow. The universality of the noise factors is classified from the macro and micro level. The influence factors including the urban spatial layout, the economic development level, the traffic policy and regulations, the traffic travel cost, the infrastructure conditions and the enterprise operation level are determined, and the relationship between the factors and the commuter travel time is analyzed. Then, the paper is made in this paper. On the basis of the characteristics of public traffic data structure, such as bus IC card data, track AFC data, bus GPS data, traffic district data and so on, using data fusion analysis technology, the extraction method of public transportation commuter travel time is put forward, which includes multi source data connection matching, trip chain structure extraction, commuter behavior discrimination. There are five steps to determine the end point of the line and calculate the travel time. The paper introduces the rules of each step in detail, determines the corresponding judgment threshold, solves the problems of the bus stop point matching on the ground bus and so on, and realizes the extraction of the commuter travel time of public transportation. Finally, the paper selects the location factors and the basic conditions of public transportation. The influence model of commuter travel time is constructed by using SPSS software. The impact model is divided into two categories according to or without the rail transit network in the traffic district. On the basis of the explanation of the two types of models, the paper quantitatively analyzes the measures to increase the density of the ground bus and rail transit network, and promote the development of the city's multi center. The important role of the commuter travel time of the public transportation shows that the average public transport commuter travel time will be reduced by about 0.37 minutes by the average density of the public transport network, and the average travel time will be reduced by about 0.37 minutes, and the average travel time will be reduced by about 1.61 minutes by the mass transit network in the residential area with rail transit, and the average travel time will be reduced by about 1.61 minutes. In the area, the density of the ground bus network increases by 1km/km2, and the average commuter travel time of the residents will be reduced by about 0.44 minutes. This study can provide decision support for the optimization of public transport network and infrastructure construction in Beijing, which is of great significance to the improvement of the commuter travel conditions of the residents.

【学位授予单位】：北京工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U491.17

【参考文献】