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Analysis and prediction of individual emissions-producing vehicle activity for light-duty vehicles and light-duty trucks on freeway entrance ramps.

机译:分析和预测高速公路入口坡道上的轻型汽车和轻型卡车的单个产生排放的汽车活动。

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摘要

The latest research into on-road vehicle emissions has shown that the level of emissions from a given vehicle is highly dependent on the mode in which it is driven. Specifically, hard accelerations and decelerations can cause extremely high levels of emissions, and the identification of the occurrence of these two driving conditions, or modes, is important to the determination of actual on-road vehicle emissions. The latest transportation air quality models have either implicitly or explicitly adopted the modal method of analysis.; This study was performed to quantify the incidence of high emissions activity on freeway entrance ramps by measuring microscopic vehicle activity with laser rangefinders. Distance measurements of 7,288 vehicles on twenty-six entrance ramps in the Louisville, Kentucky, area were taken as the vehicles traversed the ramp and entered the mainstream traffic. Approximately 12.3 million distance measurements were obtained. The distance data were later converted to speed and acceleration data that have been shown to be good indicators of elevated emissions levels.; The data were examined using linear regression, hierarchical based regression trees of vehicle activity levels against easily determined geometrical and operational characteristics of the entrance ramp. In addition, the accelerations and speeds of the vehicles were plotted against their position of the vehicle on each ramp to examine the variation in these variables due to the geometrical variables only.; The statistical analysis of the data yielded a model for predicting the incidence of microscopic vehicle activity based on geometric and operational characteristics of the roadway. Such factors as the ramp grade and the percentage of heavy duty trucks for a given ramp can then be used to predict the occurrence of high accelerations, which, in turn can be entered into modal emissions models to predict the emissions rates for a given type of entrance ramp.
机译:对道路车辆排放的最新研究表明,特定车辆的排放水平高度依赖于其驾驶方式。具体而言,猛烈的加减速会导致极高的排放,因此,确定这两种行驶条件或模式的发生对于确定实际的道路车辆排放至关重要。最新的运输空气质量模型已隐含或显式采用了模态分析方法。通过使用激光测距仪测量微观车辆活动来进行这项研究,以量化高速公路入口匝道上高排放活动的发生率。肯塔基州路易斯维尔地区的26个入口坡道上越过坡道进入主流交通时,对7288辆车进行了距离测量。获得了大约1,230万个距离测量值。距离数据随后被转换为速度和加速度数据,这些数据已被证明是排放水平升高的良好指标。使用线性回归,基于车辆活动水平的基于层次结构的回归树,根据容易确定的入口坡道的几何和操作特性,对数据进行了检查。另外,将车辆的加速度和速度相对于车辆在每个坡道上的位置作图,以检查这些变量仅由于几何变量而产生的变化。数据的统计分析产生了一个模型,用于根据道路的几何和运行特征预测微观车辆活动的发生率。然后,可以使用诸如坡度等级和给定坡道的重型卡车百分比之类的因素来预测高加速度的发生,进而可以将其输入到模式排放模型中,以预测给定类型车辆的排放率。入口坡道。

著录项

  • 作者

    Lederer, Paul Richard.;

  • 作者单位

    University of Louisville.;

  • 授予单位 University of Louisville.;
  • 学科 Engineering Civil.; Engineering Environmental.
  • 学位 Ph.D.
  • 年度 2001
  • 页码 220 p.
  • 总页数 220
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 建筑科学;环境污染及其防治;
  • 关键词

  • 入库时间 2022-08-17 11:47:09

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