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建成环境对行人交通事故严重程度的非线性影响
引用本文:戢晓峰,乔新.建成环境对行人交通事故严重程度的非线性影响[J].交通运输系统工程与信息,2023,23(1):314-323.
作者姓名:戢晓峰  乔新
作者单位:昆明理工大学,交通工程学院,昆明 650500
基金项目:国家自然科学基金(52062024);云南省创新引导与科技型企业培育计划项目(202004AR040022)
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%。

关 键 词:城市交通  行人交通事故严重程度  轻度梯度提升机  SHAP归因分析  建成环境  
收稿时间:2022-06-06

Nonlinear Influence of Built Environment on Pedestrian Traffic Accident Severity
JI Xiao-feng,QIAO Xin.Nonlinear Influence of Built Environment on Pedestrian Traffic Accident Severity[J].Transportation Systems Engineering and Information,2023,23(1):314-323.
Authors:JI Xiao-feng  QIAO Xin
Institution:Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China
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%.
Keywords:urban traffic  severity of pedestrian traffic accident  light gradient boosting machine (Light GBM)  SHAP  attribution analysis  built environment  
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