融合多源大数据的区域综合交通需求分析与对策  

Demand Analysis and Countermeasures of Regional Comprehensive Transportation Based on Multi-Source Big Data

作　　者：杨飞[1] 郭煜东 钟宇 刘振国[3,4] 谭力 王成 YANG Fei;GUO Yudong;ZHONG Yu;LIU Zhenguo;TAN Li;WANG Cheng(School of Transportation and Logistics,Southwest Jiaotong University,Chengdu 611756,China;Guiyang Transport Commission,Guiyang 550003,China;China Academy of Transportation Sciences,Beijing 100029,China;School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China;China Mobile Group Sichuan Sub-Company,Chengdu 610000,China)

机构地区：[1]西南交通大学交通运输与物流学院,四川成都611756 [2]贵阳市交通委员会,贵州贵阳550003 [3]交通运输部科学研究院,北京100029 [4]北京交通大学交通运输学院,北京100044 [5]中国移动通信集团四川有限公司,四川成都610000

出　　处：《交通运输研究》2023年第3期48-56,共9页Transport Research

基　　金：国家自然科学基金项目(52072313)。

摘　　要：随着城市间联系愈加密切,区域交通需求与日俱增。然而,区域交通出行需求与城市内部出行需求差异显著,现有城市交通调查技术与建模理论难以应用于区域层级,制约了区域交通发展规划与建设。同时,手机信令等多源交通大数据具备刻画交通特征的能力。鉴于此,首先系统分析了区域交通发展现状与既有调查技术手段,并剖析了现阶段区域交通研究面临的主要挑战,包括调查方法局限、调查内容不清晰,模型理论滞后等。然后,提出构建区域交通大数据库、研究融合手机信令数据等多源大数据的区域出行特征提取方法、探索构建区域交通模型并给出模型的基础框架等区域交通发展对策。最后,以成德眉资都市圈为例,利用手机信令数据识别成都市成华区与简阳市雁江区间通勤与非通勤情况下不同出行方式的客流。研究结果表明,目前区域交通客流以非通勤出行客流为主,小汽车仍是区域交通最主要的出行方式,研究揭示了区域交通发展特征和态势。With the increasingly close connection among cities,regional travel demand is also increasing.Since significant disparities exist between regional and urban travel demands,the current urban traffic survey technology and modeling theory are unsuitable for regional level,which restricts the planning and construction of regional transportation development.At the same time,mobile phone signaling and other multi-source traffic big data can describe the traffic status.Given this,the paper systematically analyzed the current development status and investigation technology of regional transportation and identified the main challenges faced by regional traffic research at the present stage,such as the limitations of investigation methods,unclear survey content,and outdated model theory.Then,it proposed countermeasures for regional traffic and transportation development,such as establishing a regional traffic big data database,identifying regional traffic characteristics via integrating multisource big data,constructing a regional traffic model and providing its fundamental framework.Finally,taking Chengdu-Deyang-Meishan-Ziyang Metropolitan Area as an example,it identified the commuter and non-commuter passenger flows of different travel modes between Chenghua District of Chengdu and Yanjiang District of Jianyang by using mobile phone signaling data.The research results indicate that the non-commuter passenger flow is the primary flow in regional transportation currently,while the car is the primary travel mode.The research results show the characteristics and trends of regional transportation development.

关 键 词：区域交通 交通需求 交通大数据 区域交通调查 区域交通模型 

分 类 号：U491.1[交通运输工程—交通运输规划与管理]