摘要:
为探索建成环境对行人交通事故的影响并为行人事故预防提供理论依据,本文以建成环境“5D”要素为基础,围绕土地利用、城市设计和交通系统这3个维度构建昼夜建成环境指标体系,基于轻度梯度提升机构建昼-夜间行人交通事故严重程度模型,探究城市建成环境对行人交通事故严重程度的影响机制,结合SHAP(Shapley Additive Explanation)归因分析方法揭示两者之间的非线性关系,并以深圳市为例进行实证分析。结果表明:建成环境对行人交通事故的影响效应存在显著的时段异质性;昼间行人交通事故严重程度主要受人行道可达性、地铁站可达性及学校邻近度等因素的影响;夜间行人交通事故严重程度主要受人行道可达性、娱乐兴趣点(POI)指标及道路照明条件等因素的影响。建成环境对行人交通事故严重程度存在显著的非线性影响。昼间时段学校邻近度介于[0, 3]km时,地铁站可达性小于1km时,对行人事故严重程度有较大抬升作用;夜间时段娱乐POI可达性小于0.5km时,对行人事故严重程度有抬升作用;不论昼夜,人行道可达性对行人事故严重程度均有压降作用,且临街院门密度低的区域行人事故严重程度较
高。昼-夜间模型均表现出优秀的效果,分类准确率分别为96.38%和92.08%。
Abstract:
The study on the impact of the built environment on pedestrian traffic accidents could provide a theoretical
basis for accident prevention. This paper constructed a day-night built environment index system, based on three
dimensions of land use, urban design, and transportation system in the "5D" elements. Using the light gradient boosting
machine, a day-night pedestrian traffic accident severity model was constructed to explore the influence mechanism of
the urban built environment on the severity of pedestrian traffic accidents. Combined with the SHAP attribution
analysis method, the nonlinear relationship was revealed. Taking Shenzhen City as an example, the results show that
there is significant temporal heterogeneity in the impact of the built environment on pedestrian traffic accidents. The
severity of daytime pedestrian traffic accidents is mainly affected by factors such as sidewalk accessibility, subway
station accessibility, and school proximity. At night, it is mainly affected by sidewalk accessibility, entertainment point
of interest (POI) indicators, road lighting conditions, and other factors. The built environment has a conspicuous
nonlinear effect on the severity of pedestrian traffic accidents. When the proximity of schools is between zero and three
kilometers during the daytime and the accessibility of subway stations is less than three kilometers, it has a great effect
on the severity of pedestrian accidents. When the accessibility of entertainment POI is less than 0.5 kilometers at night,
it has a significant effect on the severity of pedestrian accidents. The accessibility of sidewalks can reduce the severity
of pedestrian accidents both day and night, and the area with a low density of courtyard gates on the street has higherdegree accidents. Lastly, the model shows excellent results, with classification accuracies of 96.38% and 92.08%.
Key words:
urban traffic,
severity of pedestrian traffic accident,
light gradient boosting machine (Light GBM),
attribution analysis,
built environment
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JI Xiao-feng, QIAO Xin. Nonlinear Influence of Built Environment on Pedestrian
Traffic Accident Severity[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(1): 314-323.
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