Development of Speed Correction Factors Based on Speed-Specific Distributions of Vehicle Specific Power for Urban Restricted-Access Roadways

G. Song, Lei Yu, Yizheng Wu
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引用次数: 15

Abstract

Precise facility-specific speed correction factors (SCFs) are important parameters for direct and quick evaluation of the effect of traffic flow variations on vehicle emissions. However, the traditional method in developing SCFs is time consuming and costly, which impedes the development of SCFs and their applications. Based on massive instantaneous vehicle activity data, this paper proposes a novel method for deriving SCFs for light-duty vehicles on restricted access roadways in Beijing. First, a large sample of 60-s speed-specific trajectories is divided from the vehicle activity data, and grouped into speed-specific trajectory pools. Then, a database and two models of speed-specific and vehicle-specific power (VSP) distributions are established for different speed ranges. Further, by combining emission rates and VSP distributions, the SCFs for nitrogen oxides (NOx), hydrocarbons (HC), and carbon monoxide (CO) pollutants are derived for different emission standards. The derived SCFs from different sources of VSP distributions are compared with each other and validated by using another independent data source. The analysis result shows that, by using the VSP distribution database, the proposed method is applicable and effective in generating reliable SCFs in high resolution. The VSP distribution models can predict well SCFs within each speed range, while discontinuous predictions occur at their range boundary. Finally, several recommendations are made for future studies on developing comprehensive SCFs, which may help in practice to monitor dynamic traffic emissions when the real-time speed data are available.
基于城市限制通道车辆比功率速度比分布的速度修正因子研究
精确的设施速度校正因子(SCFs)是直接快速评价交通流变化对车辆排放影响的重要参数。然而,传统的SCFs开发方法耗时长,成本高,阻碍了SCFs的开发和应用。基于海量瞬时车辆活动数据,提出了一种基于北京市限制通道上的轻型车辆scf的计算方法。首先,从车辆活动数据中分离出60秒特定速度轨迹的大样本,并将其分组到特定速度轨迹池中。在此基础上,建立了不同车速范围下的特定车速和特定车辆功率(VSP)分布数据库和模型。此外,通过结合排放率和VSP分布,得出了不同排放标准下氮氧化物(NOx)、碳氢化合物(HC)和一氧化碳(CO)污染物的SCFs。从不同来源的VSP分布中导出的scf相互比较,并使用另一个独立的数据源进行验证。分析结果表明,利用VSP分布数据库,该方法可以有效地生成高分辨率的可靠scf。VSP分布模型可以很好地预测各个速度范围内的scf,而在其范围边界处出现不连续预测。最后,对未来发展综合可持续排放指数的研究提出了几点建议,这可能有助于在有实时速度数据的情况下监测动态交通排放。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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