Abstract
The emergence of COVID-19 pandemic makes governments around the world start to attach greater importance to the planning of Pedestrian and Bicycle Traffic Systems (PBTS)[1]. However, efficient and reasonable urban PBTS need to conform to the current situation of supply-demand differentiation of public walking or cycling, and to achieve the fairness of public access and process, which is of great significance to the improvement of the overall resilience management and the applicability of public space. But nowadays, most cities’ PBTS planning considering PBTS demand side (such as population, travel behavior, etc.) more superior to supply side (such as public transport hub)[2], at the same time, the lack of analytical data and methods used has also resulted in few studies taking into account the capacity and quality of services actually provided by urban public facilities. On this basis, this study proposed a complete PBTS planning analysis framework. In this framework, the Minimum Cumulative Resistance model (MCR) and the Geographically Weighted Regression model (GWR) were introduced as the core method of the whole analysis process. In terms of data sources, the Internet Word-of-Mouth Big Data (IWOM) is used as the basis for evaluating the ability of urban public service facilities to attract walking and bicycle behavior. In the end, the area of Huilongguan-Tiantongyuan District (H&T) in Changping District of Beijing is exemplified for empirical analysis. H&T is a residential community area with the largest population in Asia, and the tidal traffic in the region is remarkable. H&T’s simulation process of public walking and cycling behavior consists of four steps, including screening the diffusion sources of PBTS, evaluation of spatial suitability of urban walking and cycling, MCR diffusion simulation and GWE analysis. On this basis, the supply - demand analysis of H&T PBTS is completed, and further support the planning of H&T PBTS. The research found that: (1) The MCR model can analyze the suitability of spatial diffusion under the influence of multiple factors in a specific area, while the GWR model measures the relationship between different suitability results from a spatial perspective. The combination of the two can provide practical basis for the evaluation of the supply and demand status of urban PBTS. (2) IWOM big data can help us comprehensively and accurately obtain the public's satisfaction with urban public service facilities on a larger scale, although there are shortcomings in data users, urban function types and general applicability, etc. However, it cannot be denied that it provides quantitative support for the selection and diffusion simulation process of PBTS suppliers. (3) Due to the involvement of various urban built environmental factors (such as slope, urban road landscape, etc.), the framework proposed in this paper can more comprehensively analyze the impact of urban environment on PBTS planning. In the face of different urban environmental conditions, its environmental factors also need to be adjusted flexibly and appropriately in order to improve the applicability of the research framework. [1]. Moreno, C., Allam, Z., Chabaud, D., Gall, C., & Pratlong, F. (2021). Introducing the “15-Minute City”: Sustainability, Resilience and Place Identity in Future Post-Pandemic Cities. Smart Cities, 4(1), 93-111. https://doi.org/10.3390/smartcities4010006. [2]. Lagerwey, P. A., Hintze, M. J., Elliott, J. B., Toole, J. L., & Schneider, R. J. (2015). Pedestrian and bicycle transportation along existing roads—ActiveTrans priority tool guidebook (No. Project 07-17). National Cooperative Highway Research Program (Chapter 2).
