Article ID: | iaor20031106 |
Country: | United Kingdom |
Volume: | 7D |
Issue: | 2 |
Start Page Number: | 81 |
End Page Number: | 98 |
Publication Date: | Mar 2002 |
Journal: | Transportation Research. Part D, Transport and Environment |
Authors: | Guensler Randall, Hallmark Shauna L., Fomunung Ignatius |
Keywords: | statistics: regression |
The current research direction in transportation-related air-quality modeling is towards development and implementation of modal emissions models that correlate emission rates to specific ranges of activity. This paper describes a methodology to identify roadway characteristics at signalized intersections which affect the fraction of vehicle activity spend in specific operating modes where modal emission rate models indicate elevated emissions occur to improve vehicle activity inputs to modal emissions models. Field studies using laser guns were conducted on-road collecting second-by-second activity for individual vehicles at signal-controlled intersections and roadway segments. Hierarchical tree-based regression analysis was used to identify on-road geometric and operational characteristics that influenced the fractions of vehicle activity spent in specific modes. Results indicated that queue position, grade, downstream and upstream per-lane hourly volume, distance to the nearest downstream signalized intersection, percent heavy vehicles, and posted link speed limit were the most statistically significant variables.