城市交通拥塞因子时空变化特征及源解析研究

Spatial and Temporal Variation Characteristics of Urban Traffic Congestion Factors and Source Analysis

交通拥塞因子是造成“点-线-面”三级城市交通拥塞效应的重要源。为深入探究城市交通拥塞因子的时空变化特征和影响程度,本文引入用于地质和生态风险评价的相关方法。首先,基于“源-路径-目标”模型,综合考虑城市交通拥塞多变综合复杂性,深入剖析建立城市交通拥塞评价影响指标体系;其次,采用Mann-Kendall趋势检验法评估不同交通拥塞因子的时空变化趋势和突变点,利用小波分析探究周期性变化规律;改进内梅罗污染指数法对交通拥塞因子的特征及风险程度进行评估;最后,采用person相关性分析和正定矩阵因子分解(PMF)模型分析其主要来源,评估结果的不确定性。结果表明:超车、违反交通规则、随意变换车道、停车、违法违规占用道路、不良天气状况、突发交通事故这7个因子的大小变化较为明显,变异系数均超过40%;城市交通拥塞程度因子^(18)Σ_(i=1)B_(i)在1月份的早、午、晚高峰最大(11.23),3月份达到最低(8.12)。城市交通拥塞整体呈现晚高峰,早高峰,中高峰依次降低的时间变化特征,且存在8a(第1主周期)和4a(第2主周期)两个周期时间变化。内梅罗污染指数法得到的结果以中等及以上程度交通拥塞为主。研究结果可为城市交通拥塞节点治理提供科学依据。

The traffic congestion factor is an important source of urban traffic congestion at the levels of points,lines,and networks.In order to investigate the spatial and temporal characteristics of urban traffic congestion factors and their influence,this paper introduces the relevant methods for geological and ecological risk evaluation.Firstly,based on the"source-path-target"model,the multivariate and comprehensive complexity of urban traffic congestion is considered,and the impact index system of urban traffic congestion evaluation is analyzed.Secondly,the Mann-Kendall trend test was used to assess the spatial and temporal trends and abrupt change points of different traffic congestion factors,and wavelet analysis was used to explore the cyclical change pattern;To explore the law of periodic changes,an improved the Nemero pollution index method is proposed to assess the characteristics and risk degree of traffic congestion factors.Finally,Person correlation analysis and positive definite matrix factor decomposition(PMF)model are used to analyze their main sources and to assess the uncertainty of the results.The results showed that the magnitude of seven factors,namely,overtaking,traffic rule violation,random lane change,parking,illegal and illegal road occupation,adverse weather conditions,and sudden traffic accidents,varied more significantly,with coefficients of variation exceeding 40%.The urban traffic congestion degree factor^(18)Σ_(i=1)B_(i) was the largest in the morning,afternoon,and evening peaks in January(which reaches 11.23)and was the lowest in March(which reaches 8.12).The overall urban traffic congestion shows a time-varying characteristic where evening peak>morning peak>mid-peak,and there are 2 cycles of time variation of 8a(first main cycle)and 4a(second main cycle).The results obtained by the Nemero pollution index method are dominated by moderate and above traffic congestion.The results of the study can provide a scientific basis for urban traffic congestion management.