Enhancing Walking Accessibility in Urban Transportation: A Comprehensive Analysis of Influencing Factors and Mechanisms

被引:0
|
作者
Liu, Yong [1 ]
Ding, Xueqi [1 ]
Ji, Yanjie [1 ]
机构
[1] Southeast Univ, Sch Transportat, Nanjing 211189, Peoples R China
关键词
walkability; perceived accessibility; SEM; multiscale geographically weighted regression (MGWR); GEOGRAPHICALLY WEIGHTED REGRESSION; PHYSICAL-ACTIVITY; NEIGHBORHOOD WALKABILITY; PERCEIVED ACCESSIBILITY; BUILT-ENVIRONMENT; SHENZHEN; SCORE(R); STATE;
D O I
10.3390/info14110595
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 rise in "urban diseases" like population density, traffic congestion, and environmental pollution has renewed attention to urban livability. Walkability, a critical measure of pedestrian friendliness, has gained prominence in urban and transportation planning. This research delves into a comprehensive analysis of walking accessibility, examining both subjective and objective aspects. This study aims to identify the influencing factors and explore the underlying mechanisms driving walkability within a specific area. Through a questionnaire survey, residents' subjective perceptions were gathered concerning various factors such as traffic operations, walking facilities, and the living environment. Structural equation modeling was employed to analyze the collected data, revealing that travel experience significantly impacts perceived accessibility, followed by facility condition, traffic condition, and safety perception. In the objective analysis, various types of POI data served as explanatory variables, dividing the study area into grids using ArcGIS, with the Walk Score (R) as the dependent variable. Comparisons of OLS, GWR and MGWR demonstrated that MGWR yielded the most accurate fitting results. Mixed land use, shopping, hotels, residential, government, financial, and medical public services exhibited positive correlations with local walkability, while corporate enterprises and street greening showed negative correlations. These findings were attributed to the level of development, regional functions, population distribution, and supporting facility deployment, collectively influencing the walking accessibility of the area. In conclusion, this research presents crucial insights into enhancing walkability, with implications for urban planning and management, thereby enriching residents' walking travel experience and promoting sustainable transportation practices. Finally, the limitations of the thesis are discussed.
引用
收藏
页数:23
相关论文
共 50 条
  • [41] Analysis of Influencing Factors of Tourist Attractions Accessibility based on Machine Learning Algorithm
    Liu, Na
    Zhang, Hai
    INTERNATIONAL JOURNAL OF MULTIPHYSICS, 2024, 18 (03) : 803 - 812
  • [42] FACTORS INFLUENCING DELAY IN ELECTIVE MITRACLIP PROCEDURE: A COMPREHENSIVE ANALYSIS
    Raju, Apoorva
    Al Wahadneh, Omar
    Aziz, Shazia
    Alwarawrah, Zaid
    Alziadin, Nmair
    Alhalaseh, Saleh
    JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2024, 83 (13) : 1146 - 1146
  • [43] Unveiling the factors influencing financial inclusion in India: a comprehensive analysis
    Prasuna, Asha
    Kasturi, Alivelu
    Annemalla, Ramesh
    COGENT ECONOMICS & FINANCE, 2024, 12 (01):
  • [44] Factors affecting personal autonomy and perceived accessibility of people with mobility impairments in an urban transportation choice context
    Marquez, Luis
    Poveda, Juan C.
    Vega, Luis A.
    JOURNAL OF TRANSPORT & HEALTH, 2019, 14
  • [45] Factors Influencing Walking Distance to the Preferred Public Transport Stop in selected urban centres of Czechia
    Ivan, Igor
    Horak, Jiri
    Zajickova, Lenka
    Burian, Jaroslav
    Fojtik, David
    GEOSCAPE, 2019, 13 (01): : 16 - 30
  • [46] APPLICATION OF IMPROVED AHP IN THE EVALUATION OF URBAN-RURAL CONJUNCTIVE PASSENGER TRANSPORTATION INFLUENCING FACTORS
    Guo, Bao-Zhen
    Zhang, Xin-Rui
    PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-6, 2009, : 2499 - 2503
  • [47] Wax Deposition during the Transportation of Waxy Crude Oil: Mechanisms, Influencing Factors, Modeling, and Outlook
    Zhu, Haoran
    Lei, Yun
    Yu, Pengfei
    Li, Chuanxian
    Yang, Fei
    Yao, Bo
    Yang, Shuang
    Peng, Haoping
    ENERGY & FUELS, 2024, 38 (11) : 9131 - 9152
  • [48] An Open Transportation Network Resilience Analytics Platform for Large-Scale Urban Accessibility Analysis
    Castro, Edgar
    Wang, Qi
    Akhavan, Armin
    CONSTRUCTION RESEARCH CONGRESS 2018: INFRASTRUCTURE AND FACILITY MANAGEMENT, 2018, : 213 - 221
  • [49] Investigating the factors influencing urban residents' low-carbon travel intention: A comprehensive analysis based on the TPB model
    Liao, Caisheng
    Huang, Yongkai
    Zheng, Zhenwen
    Xu, Yihai
    TRANSPORTATION RESEARCH INTERDISCIPLINARY PERSPECTIVES, 2023, 22
  • [50] Influencing Factors Analysis on Sunken Greenbelt Design of Urban Road
    Zhang, Huzhu
    Li, Huimin
    PROGRESS IN INDUSTRIAL AND CIVIL ENGINEERING III, PT 1, 2014, 638-640 : 1158 - +