论文总字数：47157字

摘 要

近几年来，我国经济社会迅速发展，随之而来的是城市化与机动化进程的迈进，城市交通逐渐趋于饱和。拥堵、污染、交通事故等城市交通问题慢慢出现并变得严重。为了解决日益加剧的城市交通问题，大力发展公共交通成了一剂良方。显然，与传统的私人交通方式相比，公共交通具有运量大、效率高、污染少等众多优点，而为了更好的发展城市公共交通，提高城市公共交通的信息化与智能化水平，使之更好的服务群众，我们交通领域必须深入了解基于个人及群体的出现需求和出行特征，来指导和改进城市公共交通的发展。

为了收集公共交通的基础数据，传统的收集方法十分依赖人工，主要以发问卷和单体调查的方法进行。这样的方法不仅需要大量的人力物力与财力，得到结果也十分受到调查人员的投入程度与被调查人员的配合程度等随机因素的影响。随着电子收费系统开始在城市公共交通中得到广泛的应用，越来越多的城市居民在进出站时选择使用刷智能卡的方式付费。智能卡记录数据的准确性给我们数据处理带来了极大的便利，并且增长了数据的时间跨度。如果能在此基础上分析居民的出行需求与出行特征，将给城市公共交通的发展带来新的契机。

本文首先对国内外在进行基于智能卡的公交需求分析方面的文献进行了综述研究，从城市智能卡的推广使用、公交智能卡数据的采集和公交出行OD矩阵推导及特征分析三个方面展开，确定了研究内容与研究难点，并制定了技术路线。接着，基于现有的深圳市2016年的地铁刷卡记录数据，选择数据的分析手段开展研究。研究的重点在于公交需求的生成，为了完成此目标，首先对智能卡的公交数据进行预处理，筛选错误的信息及残缺的信息，然后进行OD矩阵的推导，确定对应的上车站点、下车站点、对数据中换乘和短期活动进行判定、进而生成一天及全年的OD矩阵。生成后，选择一定的方法进行矩阵的验证，并在此基础上分析深圳市的公交需求。然后，为了进行更加深入的研究，针对大数据中某个特定的智能卡持有者进行出行分析，选择一个常出现的智能卡ID，分析个人的出行时空规律，进行一些时空图的绘制，深入思考不同出行群体的不同地铁出行需求。

关键词：智能卡数据 出行OD矩阵 公交需求 时空分析

Abstract

In recent years, along with the Chinese rapid economic and social development, followed by the process of urbanization and mobility, urban traffic is gradually becoming saturated. Traffic congestion, traffic pollution, traffic accidents and other urban traffic problems slowly appear and become serious. In order to solve the increasingly serious urban traffic problem, the development of public transport has become a panacea. Obviously, compared with the traditional way of private transport, public transport has many advantages, such as large volume, high efficiency and less pollution. In order to better developing urban public transport, improve the informatization and intelligence level of urban public transport, and make it better serve the masses, we must have an in-depth understanding of the needs and characteristics of individuals and groups on their travelling to guide and improve the development of urban public transport.

For the collection of basic data of public transportation, the traditional method relies on the artificial work, mainly by questionnaire and monomer survey. Such a method not only needs a lot of human and financial resources, the results are also affected by the degree of involvement of investigators, the degree of coordination of the survey-takers and other random factors. With the development of information technology, electronic toll systems have been widely used in urban public transportation. More and more urban residents choose to use smart card to pay when they enter and leave the station. The accuracy of the data recorded by smart card has brought great convenience to data processing, and has increased the data time span. If we can analyze the residents ' travel needs and characteristics on this basis, it will bring new opportunity for the development of urban public transportation.

Firstly, this paper summarizes and studies the literature on the demand analysis of public transport based on smart card at home and abroad. From the following three aspects, popularization and use of the city smart card, the data collection of the public traffic and the derivation of the OD matrix of the public transport trip and the characteristic analysis, the paper determines the research content and the difficulties. Then, based on the existing Shenzhen City 2016 Subway smart card data, the paper selects data analysis method to carry out research. The focus of the study is the generation of the public transport needs. For the sake of achieving this goal, first of all, we need to preprocess the smart card data, filtering the wrong information and incomplete information, and then derivate the OD matrix, determining the corresponding boarding site, alighting site, the transfer and short-term activities, and then generate the OD matrix for the day and year. After the generation, a certain method is chosen to verify the matrix. On this basis, the Shenzhen public transport demand is analyzed. For the purpose of carrying out a more in-depth study, a particular smart card holder is selected in large data, choosing a common smart card ID and analyzing the individual travel spatial-temporal law to make some spatial-temporal mapping, deeply considering the different travel needs of different travel groups.

KEY WORDS: Smart card data, transport travel OD matrix, public transport demand, spatial-temporal analysis

目录

摘要 I

Abstract II

第一章 绪论 1

1.1 研究背景及意义 1

1.1.1 研究背景 1

1.1.2 研究意义 2

1.2 国内外研究现状 2

1.3 研究内容与研究难点分析 5

1.3.1 研究内容 5

1.3.2 研究难点分析 6

1.4 技术路线 7

1.5 本章小结 7

第二章 公交数据的采集与分析 8

2.1 传统数据采集方法 8

2.1.1 跟车调查 8

2.1.2 驻站调查 8

2.1.3 问卷调查 8

2.1.4 小票调查 9

2.2 传统数据采集方法优缺点 9

2.3 现代数据采集方法 10

2.3.1 基于图像拍摄的数据采集方法 10

2.3.2 基于传感器的数据采集方法 10

2.3.3 基于GPS与GIS技术的数据采集方法 11

2.3.4 基于智能卡的数据采集方法 12

2.4 数据分析手段 13

2.5 本章小结 14

第三章 基于智能卡数据的公交需求分析 15

3.1 智能卡数据分析 15

3.1.1 智能卡数据结构 15

3.1.2 智能卡数据的选择 17

3.2 智能卡数据的预处理 17

3.2.1 数据格式处理 17

3.2.2 数据错误清理 18

3.3 基于智能卡数据的OD矩阵的推导 18

3.3.1 上下车站点的推导 18

3.3.2 公交换乘行为的分析 20

3.3.3 基于地铁站所的深圳市分区 21

3.3.4 OD矩阵的生成 24

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