Urban link travel speed dataset from a megacity road network

被引：24
|
作者：
Guo, Feng [1 ]
Zhang, Dongqing [1 ]
Dong, Yucheng [1 ]
Guo, Zhaoxia [1 ]
机构：
[1] Sichuan Univ, Sch Business, Chengdu 610065, Sichuan, Peoples R China
来源：
SCIENTIFIC DATA | 2019年 / 6卷 / 1期
基金：
中国国家自然科学基金;
关键词：
MODEL;
D O I：
10.1038/s41597-019-0060-3
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Link travel speeds in road networks are fundamental data in many research areas of traffic, transportation, and logistics. To support the research in these areas, we develop a dataset, containing the travel speeds on each road link and in different time periods together with the real road network map. The dataset is collected from a representative megacity in Western China, Chengdu. The road network of this city involves different urban road network structures. The dataset shows the realistic variations and randomness of urban link travel speeds. This enables the research of real data-driven decision-making problems in traffic, transportation and logistics areas.
引用
收藏
页数：8
相关论文
共 50 条
  • [41] Congestion recognition for hybrid urban road systems via digraph convolutional network
    Han, Xiao
    Shen, Guojiang
    Yang, Xi
    Kong, Xiangjie
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2020, 121
  • [42] Traffic Estimation for Large Urban Road Network with High Missing Data Ratio
    Offor, Kennedy John
    Vaci, Lubos
    Mihaylova, Lyudmila S.
    SENSORS, 2019, 19 (12)
  • [43] Assessing Urban Road Network Capacity considering Parking Supply and Parking Pricing
    Jiang, Xiaowei
    Du, Muqing
    Liu, Haisheng
    JOURNAL OF ADVANCED TRANSPORTATION, 2020, 2020
  • [44] Fugitive Dust Emissions from Paved Road Travel in the Lake Tahoe Basin
    Zhu, Dongzi
    Kuhns, Hampden D.
    Brown, Scott
    Gillies, John A.
    Etyemezian, Vicken
    Gertler, Alan W.
    JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION, 2009, 59 (10) : 1219 - 1229
  • [45] The planning and design of road network structure in urban railway transit hub areas
    Cai, Zhaoyang
    Yan, Jianwei
    INTERNATIONAL JOURNAL OF LOW-CARBON TECHNOLOGIES, 2018, 13 (03) : 198 - 203
  • [46] Estimation of vessel link-level travel time distribution: A directed network-driven approach
    Liang, Maohan
    Su, Jianlong
    Gao, Ruobin
    Liu, Ryan Wen
    Zhan, Yang
    OCEAN ENGINEERING, 2024, 313
  • [47] Short-term speed predictions exploiting big data on large urban road networks
    Fusco, Gaetano
    Colombaroni, Chiara
    Isaenko, Natalia
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2016, 73 : 183 - 201
  • [48] Forecasting urban electric vehicle charging power demand based on travel trajectory simulation in the realistic urban street network
    Mahmoudi, Eslam
    Barros, Tarcio Andre dos Santos
    Ruppert Filho, Ernesto
    ENERGY REPORTS, 2024, 11 : 4254 - 4276
  • [49] MCAGCN: Multi-component attention graph convolutional neural network for road travel time prediction
    Zhao, Zhihua
    Li, Chao
    Zhang, Xue
    Xie, Nengfu
    Zeng, Qingtian
    IET INTELLIGENT TRANSPORT SYSTEMS, 2024, 18 (01) : 139 - 153
  • [50] Spatial characteristics of carbon dioxide emission intensity of urban road traffic and driving factors: Road network and land use
    Yang, Yang
    Takase, Tatsuo
    SUSTAINABLE CITIES AND SOCIETY, 2024, 113
12345