A Clustering Analysis of Speed Distributions and Emission Estimation Based on Traffic Performance Index
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摘要: 交通拥堵评价指标与机动车排放强度的关系缺乏论述.利用北京市浮动车数据,处理成分道路等级的交通运行指数与速度分布数据.以车辆排放测试数据、工况数据为基础,量化速度与排放因子间的关系.分析交通运行指数与排放因子的测算机理,选择速度为中间变量,建立二者的关系量化模型.为降低交通运行指数与排放因子关系的不确定性,结合速度分布的影响因素,利用K-Means聚类方法,对交通运行指数与速度分布数据聚类分析.研究发现按道路等级、交通规律相似的工作日/周末以及时间段(6:00-12:00时,12:00-22:00时,22:00-6:00时)交叉组合分类,快速路、主干路、次支路速度分布不确定性分别降低了10.1%、13.6%、14.6%,排放因子不确定性分别降低了10.1%,13.4%,14.2%.测算了各分类条件下交通运行指数与排放因子间的定量关系.Abstract: Few efforts have been made to quantitatively analyze the relationship between traffic congestion index (TCI) and emissions in urban traffic networks.This study develops a method to derive speed distributions for TPI-specific traffic patterns based on massive floating car data (FCD).The relationship between speed and emission factors is quantified based on massive data of vehicle activity and emissions.After analyzing influencing factors of traffic performance index (TPI) and emission factors,speed distribution is identified as a bridging parameter between TPI and emission factors.In order to reduce the uncertainty of the TPbderived emission factors,a K-Means clustering method is applied to classify speed distributions of the TPI-specific traffic pattern by analyzing factors influencing speed distribution.It turns out that when sample data is clustered by road classes,weekdays/weekends,time periods (06:00-12:00,12:00-22:00 and 22:00-06:00),the coefficient of variation of speed distribution (CVSD) decrease by 10.1 %,13.6 %,and 14.6 %,respectively and the coefficient of variation of emission factor (CVEF) decrease by 10.1%,13.4%,and 14.2%,respectively.Emission factors of the TPI-specific traffic pattern for different classes of roads are calculated under different clustering criteria.
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