基于手机定位信息和出行调查的动态OD获取方法

发布时间：2019-06-03 19:24

【摘要】：摘要：作为对一定时间范围内交通需求描述的OD矩阵,是现代化城市交通研究中必不可少的部分。随着信息化进程的加快,利用手机定位信息获取交通信息已经成为可能。但目前对手机定位信息的研究还多局限于理论建模阶段,并且出行识别技术尚未成熟。基于此,本文将基于手机定位信息以及辅助的出行调查信息,开展基于典型区域的动态OD获取方法研究。首先,本研究针对现有的OD估计方法展开综述研究,并且对OD估计的数据采集方法进行研究,分析和总结了现存方法的优缺点。进而总结了现阶段手机定位技术的研究现状。在此基础上,确定了本文研究内容。其次,针对手机定位信息和出行调查信息,分别进行了对原始数据的分析,以及交通OD信息的提取。针对手机定位信息,本研究在分析数据特性的基础上,设计了基于手机定位信息的出行链获取方法,通过速度阈值、时间阈值以及距离阈值的限定,对OD点进行识别。然后,本研究重点分析了手机定位信息的触发机制,并依据该机制,将手机定位信息划分为主动方式和被动方式。在此基础上,本研究对两种方式的时间分布特征进行了分析,得到了不同方式下的24小时时变特征,从而总结了两种不同触发机制下数据的优缺点。进而,针对主动方式和被动方式分别设计了基于出行调查数据的OD矩阵修正方法。对于主动方式触发的OD数据,首先根据OD总量时变规律进行修正,进而对单个OD对进行分别的调整。对于被动方式触发的OD数据,根据其自身的数据特性,本研究依据出行调查的OD矩阵数据,利用手机OD的时变规律曲线,设计了修正方法。最后,本研究以典型区域为例进行了动态OD获取方法的验证。对区域界定后的典型区进行原始OD数据的获取,并按照修正方法,进行基于出行调查数据的OD矩阵修正。对全方式触发的OD矩阵数据以及被动方式触发的OD矩阵数据分别进行不同维度的验证。从出行总量维度分析,修正之后的误差从原先的30.08%降低到7.11%。从小区间产生吸引关系来看,一维相关系数都有明显提升。从矩阵相关性分析,虽然也有提升,但提升幅度不明显,这可能与数据来源的技术差异以及研究过程中的假设有关。
[Abstract]:Abstract: as the OD matrix of traffic demand description in a certain time range, it is an indispensable part of modern urban traffic research. With the acceleration of information process, it is possible to use mobile phone positioning information to obtain traffic information. However, at present, most of the research on mobile phone location information is limited to the theoretical modeling stage, and the travel identification technology is not yet mature. Based on this, this paper will carry out the research of dynamic OD acquisition method based on typical area based on mobile phone location information and auxiliary travel survey information. First of all, this study summarizes the existing OD estimation methods, and studies the data acquisition methods of OD estimation, and analyzes and summarizes the advantages and disadvantages of the existing methods. Then the research status of mobile phone positioning technology is summarized. On this basis, the research content of this paper is determined. Secondly, according to the mobile phone positioning information and travel survey information, the original data are analyzed and the traffic OD information is extracted. Aiming at the mobile phone positioning information, based on the analysis of the data characteristics, this study designs a mobile phone positioning information based on the departure chain acquisition method, through the speed threshold, time threshold and distance threshold limit, the ODpoint is identified. Then, this study focuses on the trigger mechanism of mobile phone positioning information, and according to this mechanism, the mobile phone positioning information is divided into active mode and passive mode. On this basis, the time distribution characteristics of the two methods are analyzed, and the 24-hour time-varying characteristics under different modes are obtained, and the advantages and disadvantages of the data under two different trigger mechanisms are summarized. Furthermore, the OD matrix correction method based on travel survey data is designed for active mode and passive mode respectively. For the OD data triggered by active mode, the total amount of OD is modified according to the time-varying law, and then the single OD pair is adjusted separately. For the passively triggered OD data, according to its own data characteristics, based on the OD matrix data of travel survey, using the time-varying law curve of mobile phone OD, a correction method is designed. Finally, the dynamic OD acquisition method is verified by taking the typical region as an example. The original OD data are obtained from the typical area after the region is defined, and the OD matrix based on travel survey data is modified according to the correction method. The OD matrix data triggered by the whole mode and the OD matrix data triggered by the passive mode are verified in different dimensions. From the dimension of the total amount of travel, the corrected error is reduced from 30.08% to 7.11%. From the point of view of attraction relationship in small interval, the one-dimensional correlation coefficient has been obviously improved. From the matrix correlation analysis, although there is also improvement, but the extent of improvement is not obvious, which may be related to the technical differences of data sources and the assumptions in the research process.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U491.11;U495

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