Nonlinear impact analysis of built environment on urban road traffic safety risk

IF 3.2 Q2 AUTOMATION & CONTROL SYSTEMS
Zhang Yaofang, Chen Jian, Qiu Zhixuan
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引用次数: 0

Abstract

With the rapid development of economy, the increasing number of motor vehicles and the total road mileage, which leads to the increasingly prominent traffic safety problems. In order to explore the quantitative relationship between the built environment and the risk of urban road traffic safety, this paper reconstructs the built environment system based on the ‘5D' element model of the built environment combined with the factors influencing traffic safety risks, and describes the built environment from multiple aspects such as density, diversity &traffic design etc, and then build the gradient lift decision tree model to explore the importance and dependency of variables. The empirical analysis selects a district in Chongqing as the research unit, and the results show that: the RMSE the model was 0.0036, the MAPE was 1.9%, and the determination coefficient R2 was 0.84. GBDT algorithm results shows: the cumulative importance of population density, road facilities, intersection density, secondary road and branch road density, average intersection distance, land use mix, and economic density reaches 77.87%. Some variables show obvious nonlinearity and threshold effect.
建筑环境对城市道路交通安全风险的非线性影响分析
随着经济的快速发展,机动车数量和道路总里程不断增加,从而导致交通安全问题日益突出。为了探究已建成环境与城市道路交通安全风险之间的定量关系,本文基于已建成环境的“5D”要素模型,结合影响交通安全风险的因素,重构了已建成环境系统,从密度、多样性、交通设计等多个方面对已建成环境进行了描述。然后建立梯度提升决策树模型来探讨变量的重要性和依赖性。实证分析选取重庆市某区为研究单位,结果表明:模型的RMSE为0.0036,MAPE为1.9%,决定系数R2为0.84。GBDT算法结果表明:人口密度、道路设施、交叉口密度、次级道路和分支道路密度、平均交叉口距离、土地利用结构、经济密度的累积重要性达到77.87%。部分变量表现出明显的非线性和阈值效应。
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来源期刊
Systems Science & Control Engineering
Systems Science & Control Engineering AUTOMATION & CONTROL SYSTEMS-
CiteScore
9.50
自引率
2.40%
发文量
70
审稿时长
29 weeks
期刊介绍: Systems Science & Control Engineering is a world-leading fully open access journal covering all areas of theoretical and applied systems science and control engineering. The journal encourages the submission of original articles, reviews and short communications in areas including, but not limited to: · artificial intelligence · complex systems · complex networks · control theory · control applications · cybernetics · dynamical systems theory · operations research · systems biology · systems dynamics · systems ecology · systems engineering · systems psychology · systems theory
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