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Association between built environment characteristics and school run traffic congestion in Beijing, China

Chaogui Kang, Xiaxin Wu, Jialei Shi, Chao Yang

Abstract

School-escorted trips are a significant contributor to traffic congestion. Existing studies mainly compare road traffic during student pick-up/drop-off hours with off-peak times, often overlooking the fact that school-run traffic congestion is unevenly distributed across areas with different built environment characteristics. We examine the relationship between the built environment and school-run traffic congestion, using Beijing, China, as a case study. First, we use multi-source geospatial data to assess the built environment characteristics around schools across five dimensions: spatial concentration, transportation infrastructure, street topology, spatial richness, and scenescapes. Second, employing a generalized ordered logit model, we analyze how traffic congestion around schools varies during peak hours on school days, regular non-school days, and national college entrance exam days. Lastly, we identify the built environment factors contributing to school-run traffic congestion through multivariable linear regression and Shapley value explanations. Our findings reveal that: (1) School runs significantly exacerbate traffic congestion around schools, reducing the likelihood of free-flow by 8.34\% during school run times; (2) School-run traffic congestion is more severe in areas with multiple schools, bus stops, and scenescapes related to business and financial functions. These insights can inform the planning of new schools and urban upgrade strategies aimed at reducing traffic congestion.

Association between built environment characteristics and school run traffic congestion in Beijing, China

Abstract

School-escorted trips are a significant contributor to traffic congestion. Existing studies mainly compare road traffic during student pick-up/drop-off hours with off-peak times, often overlooking the fact that school-run traffic congestion is unevenly distributed across areas with different built environment characteristics. We examine the relationship between the built environment and school-run traffic congestion, using Beijing, China, as a case study. First, we use multi-source geospatial data to assess the built environment characteristics around schools across five dimensions: spatial concentration, transportation infrastructure, street topology, spatial richness, and scenescapes. Second, employing a generalized ordered logit model, we analyze how traffic congestion around schools varies during peak hours on school days, regular non-school days, and national college entrance exam days. Lastly, we identify the built environment factors contributing to school-run traffic congestion through multivariable linear regression and Shapley value explanations. Our findings reveal that: (1) School runs significantly exacerbate traffic congestion around schools, reducing the likelihood of free-flow by 8.34\% during school run times; (2) School-run traffic congestion is more severe in areas with multiple schools, bus stops, and scenescapes related to business and financial functions. These insights can inform the planning of new schools and urban upgrade strategies aimed at reducing traffic congestion.

Paper Structure

This paper contains 25 sections, 6 equations, 8 figures, 3 tables.

Figures (8)

  • Figure 1: The spatial distribution of primary and secondary schools within the case studied area. To count the number of schools in the vicinity of roads by category, we use a buffer area in the range of 500 meters away from the road.
  • Figure A-1: The distribution of SHAP interaction values of scenescape 1 on scenescape 7
  • Figure A-2: The distribution of SHAP interaction values of scenescape 6 on scenescape 5
  • Figure A-3: The distribution of SHAP interaction values of scenescape 6 on scenescape 7
  • Figure A-4: The distribution of SHAP interaction values of scenescape 6 on scenescape 9
  • ...and 3 more figures