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

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.