基于成都市公交IC卡数据的公交客流量分析

发布时间：2018-07-05 00:58

本文选题：公共交通 + 公交客流　；参考：《西南交通大学》2015年硕士论文

【摘要】：一座城镇的公交客流特征可以反映该城镇居民乘坐公交车出行的时间和空间分布状况,能够支撑城镇居民对公交车需求方面的研究,为城镇公共交通系统的实时调度与优化提供依据,是城镇公共交通体系升级地一块基石。与传统客流量分析方法相比,基于智能公交系统提供的大量刷卡数据而进行的公交客流特征分析更具精准性、全面性和可行性。本论文以成都市市区主干公交线路为研究对象,基于成都市智能公交IC卡记录的刷卡消费数据,首先利用公交车一次出行时乘客上车刷卡的时间序列提出一种估计乘客上车站点的可行方法；然后应用和扩展该方法用于估计成都市单条公交线路在一天中每位持卡消费乘客的上车站点；最后估计成都市市区所有主干线路一天刷卡乘客的上车站点,并分析主干线路所有公交站点处的上车客流量特征。本论文使用MATLAB 7.13编程软件进行数据分析处理以及算法实现,并从以下三个方面进行详细的研究：第一,研究在缺少公交车辆GPS数据情况下如何利用公交IC卡刷卡数据估计乘客上车站点。通过收集成都市市区主干公交线路名称、站点名称以及站点经纬度等基础信息,抽取一条公交线路一个月的公交IC卡刷卡消费数据,不依赖于车辆GPS定位数据,采用聚类方法分析上车时间序列从而建立估计乘客上车站点的理论模型,并跟车记录该条线路上公交车的实际载客数据信息,以此验证所提理论方法的可行性。第二,研究公交客流量在单条公交线路上的分布特征。详细阐述了单条公交线路上的客流在时间维度上的差异性和周期波动性。第三,研究公交客流量在公交站点上的分布特征。具体分析了成都市市区主干公交线路上所有站点在不同时间段内的上车客流量,以及在相同时间段内,上车客流量在各个站点的不同分布。
[Abstract]:The characteristics of public transport passenger flow in a town can reflect the time and space distribution of the residents travelling by bus, and can support the study on the demand for buses by urban residents. Providing the basis for the real-time scheduling and optimization of urban public transportation system is a cornerstone of the upgrading of urban public transportation system. Compared with the traditional passenger flow analysis method, the characteristic analysis of bus passenger flow based on a large amount of card swipe data provided by intelligent bus system is more accurate, comprehensive and feasible. This paper takes the main bus route in Chengdu as the research object, based on the IC card data of smart bus in Chengdu. Firstly, a feasible method of estimating passenger boarding station is presented by using the time series of commuters swiping their cards on board during a bus trip. Then the method is used to estimate the boarding station of each card consumer passenger on a single bus line in Chengdu in one day, and finally to estimate the boarding station of all trunk lines in Chengdu city in one day by swiping card passengers. And analysis of the trunk line at all bus stops on the passenger flow characteristics. This thesis uses the MATLAB 7.13 programming software to carry on the data analysis processing as well as the algorithm realization, and carries on the detailed research from the following three aspects: first, In the absence of GPS data of public transport vehicles, how to estimate passenger boarding stations using IC card data is studied. By collecting the basic information such as the name of the main bus line, the name of the station and the latitude and longitude of the station in Chengdu, the paper extracts the IC card consumption data of a public transport line for one month, and does not depend on the GPS positioning data of the vehicle. The theoretical model of estimating passenger boarding station is established by using clustering method to analyze boarding time series, and the actual carrying data information of bus on this line is recorded with the vehicle to verify the feasibility of the proposed theoretical method. Secondly, the distribution characteristics of bus passenger flow on a single bus line are studied. The difference and cycle fluctuation of passenger flow on single bus line in time dimension are expounded in detail. Thirdly, the distribution characteristics of bus passenger flow at bus stations are studied. This paper analyzes the passenger flow of all stations on the main bus line in Chengdu city in different time periods, and the different distribution of passenger flow in different stations in the same time period.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U492.413

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