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Analysis of Urban Congestion Traceability: The Role of the Built Environment

Author

Listed:
  • Chenguang Li

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

  • Duo Wang

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

  • Hong Chen

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

  • Enze Liu

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

Abstract

Analyzing the factors influencing traffic congestion is essential for urban planning and coordinated development. Previous research frequently focuses on the internal aspects of traffic systems, often overlooking the impact of external factors on congestion sources. Therefore, this study utilizes a geospatial dataset and mobile signaling data, firstly applying the Fuzzy C-Means (FCM) algorithm to identify congested roads of different levels and trace the localization of travelers’ origins on regional congested roads. Furthermore, it employs the LightGBM method to study the influence of the built environment of various congestion sources on network-level congestion. The findings are as follows: (1) There is a positive correlation between traffic congestion and geographical location, with congestion predominantly caused by a few specific plots and demonstrating a concentrated trend in city centers. (2) Residential population density is the most critical factor, accounting for over 12% of the congestion contribution, followed by road density and working population density. (3) Both residential and working population densities show a non-linear positive correlation with congestion contribution, while the mixture of land use displays a non-linear V-shaped influence. Additionally, when residential population density is between 8000 and 11,000, it notably exacerbates congestion contribution. Significantly, by emphasizing land use considerations in traffic system analysis, these findings illuminate the intricate linkages between urban planning and traffic congestion, advocating for a more comprehensive approach to urban development strategies.

Suggested Citation

  • Chenguang Li & Duo Wang & Hong Chen & Enze Liu, 2024. "Analysis of Urban Congestion Traceability: The Role of the Built Environment," Land, MDPI, vol. 13(2), pages 1-15, February.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:2:p:255-:d:1341230
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    References listed on IDEAS

    as
    1. Zhikang Bao & Yifu Ou & Shuangzhou Chen & Ting Wang, 2022. "Land Use Impacts on Traffic Congestion Patterns: A Tale of a Northwestern Chinese City," Land, MDPI, vol. 11(12), pages 1-17, December.
    2. Chao Sun & Jian Lu, 2022. "The Relative Roles of Socioeconomic Factors and Governance Policies in Urban Traffic Congestion: A Global Perspective," Land, MDPI, vol. 11(10), pages 1-17, September.
    3. Duo Wang & Hong Chen & Chenguang Li & Enze Liu, 2023. "Exploring the Relationship between Land Use and Congestion Source in Xi’an: A Multisource Data Analysis Approach," Sustainability, MDPI, vol. 15(12), pages 1-15, June.
    4. Liu, Jixiang & Xiao, Longzhu, 2023. "Non-linear relationships between built environment and commuting duration of migrants and locals," Journal of Transport Geography, Elsevier, vol. 106(C).
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    Cited by:

    1. Chaojie Duan & Shuhong Ma & Chenguang Li, 2024. "Exploring the Impact of Built Environment on Elderly Metro Ridership at Station-to-Station Level," Sustainability, MDPI, vol. 16(23), pages 1-15, November.

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