A Spatio-Temporal Perspective on Commercial Vehicle Travel Patterns in Urban Environments

被引:1
作者
Qin, Jianxin [1 ,2 ]
Lin, Yuan [1 ,2 ]
Wu, Tao [1 ,2 ]
Lin, Xinyi [1 ,2 ]
Li, Xiaolong [3 ]
机构
[1] Hunan Normal Univ, Hunan Key Lab Geospatial Big Data Min & Applicat, Changsha 410081, Peoples R China
[2] Hunan Normal Univ, Sch Geog Sci, Changsha 410081, Peoples R China
[3] East China Univ Technol, Key Lab Mine Environm Monitoring & Improving Poya, Minist Nat Resources, Nanchang 330013, Peoples R China
来源
IEEE ACCESS | 2024年 / 12卷
关键词
Urban areas; Trajectory; Matrix decomposition; Global Positioning System; Public transportation; Feature extraction; Data mining; Traffic control; Singular value decomposition; Urban functional area interaction; vehicle travel patterns; spatio-temporal data analysis; singular value decomposition (SVD); SPATIAL STRUCTURE;
D O I
10.1109/ACCESS.2024.3421554
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The relationship between commercial vehicle travel patterns and urban functional areas reveals potential connections between urban form and human geographic flows, which provides critical information for optimizing urban transportation systems. Benefiting from the large-scale trajectory datasets, it would be possible to investigate deeper research by modeling the implied urban travel patterns. This study designs a framework to reveal the collective movement patterns of commercial vehicle trajectories inside the urban environment, focusing on their spatiotemporal variations within functional areas. Stopping behaviors of trajectories were identified to construct spatiotemporal origin-destination (OD) matrices, representing time-varying human geographic flows. The singular value decomposition (SVD) method was employed to quantify spatio-temporal OD matrice to obtain time and space travel features. Travel patterns' dynamics and spatial interactions within functional areas were then analyzed. The experimental results obtained with real-life datasets from Changsha, China, uncovered three typical travel patterns depicting commercial vehicle activities in urban environment shifts from work-related locations on weekdays to leisure destinations on weekends, with central areas experiencing more short and medium-range trips. The findings provide scientific references for optimizing spatio-temporal travel patterns and functional distribution to meet the demands of urban development and traffic management strategies.
引用
收藏
页码:91447 / 91461
页数:15
相关论文
共 45 条
  • [1] Smart Cities from the Perspective of Systems
    Ammara, Umme
    Rasheed, Khansa
    Mansoor, Athar
    Al-Fuqaha, Ala
    Qadir, Junaid
    [J]. SYSTEMS, 2022, 10 (03):
  • [2] Rec-CFSVD plus plus : Implementing Recommendation System Using Collaborative Filtering and Singular Value Decomposition (SVD) plus
    Anwar, Taushif
    Uma, V.
    Srivastava, Gautam
    [J]. INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, 2021, 20 (04) : 1075 - 1093
  • [3] An End-to-End Curriculum Learning Approach for Autonomous Driving Scenarios
    Anzalone, Luca
    Barra, Paola
    Barra, Silvio
    Castiglione, Aniello
    Nappi, Michele
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (10) : 19817 - 19826
  • [4] Fatigue in long-duration travel diaries
    Axhausen, K. W.
    Loechl, M.
    Schlich, R.
    Buhl, T.
    Widmer, P.
    [J]. TRANSPORTATION, 2007, 34 (02) : 143 - 160
  • [5] Baek D, 2024, Arxiv, DOI arXiv:2403.01233
  • [6] Cities in the Developing World
    Bryan, Gharad
    Glaeser, Edward
    Tsivanidis, Nick
    [J]. ANNUAL REVIEW OF ECONOMICS, VOL 12, 2020, 12 : 273 - 297
  • [7] Analysis of the Cycling Flow Between Origin and Destination for Dockless Shared Bicycles Based on Singular Value Decomposition
    Cao, Min
    Cai, Boqin
    Ma, Shangjing
    Lu, Guonian
    Chen, Min
    [J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2019, 8 (12)
  • [8] [陈勐韬 Chan Mengtao], 2020, [地球物理学进展, Progress in Geophysiscs], V35, P940
  • [9] Chao Yang, 2015, Applied Mechanics and Materials, V743, P422, DOI 10.4028/www.scientific.net/AMM.743.422
  • [10] Clustering Vehicle Temporal and Spatial Travel Behavior Using License Plate Recognition Data
    Chen, Huiyu
    Yang, Chao
    Xu, Xiangdong
    [J]. JOURNAL OF ADVANCED TRANSPORTATION, 2017,