An Empirical Study of the Relationships Between Macroscopic Traffic Parameters and Vehicle Emissions

Understanding the relation between traffic parameters and vehicle emissions is an important step toward reducing the potential for global warming, smog, ozone depletion, and respiratory illness. Traffic engineers, through improved roadway design and traffic control, have the ability to reduce vehicle emissions. However, current vehicle emissions models do not allow traffic analysts to easily and accurately predict vehicle emissions based on commonly used macroscopic traffic parameters (i.e., control delay, corridor stops, average speed).The primary purpose of this thesis is to develop a corridor-level methodology for quantifying the individual effects of delay and stops on hydrocarbon (HC), nitric oxide (NO), and carbon monoxide (CO) vehicle emissions. A secondary, but equally important, purpose is to evaluate the impact of signal coordination on vehicle emissions through a before and after study. This is an important funding issue because signal coordination projects currently receive CMAQ funding with the expectation of a reduction in vehicle emissions.The study focused on three signalized arterials in Research Triangle Park and Cary, North Carolina. The data collection procedure differed from the majority of past emissions research in focusing on the collection of real-world, on-road data from instrumented vehicles. Sixteen different vehicles and ten drivers were tested, resulting in a total of approximately 825 corridor runs, 140 vehicle-hours, and 3,060 vehicle-miles of simultaneous vehicle emissions and engine diagnostic data. The latter were manipulated to produce macroscopic traffic parameters such as free flow speed, delays, and stops.An important result from this thesis is that vehicle emissions are generally highest while vehicles are accelerating and lowest while idling. In addition, control delay and corridor stops have a quantifiable effect on vehicle emissions, as an increase in control delay and corridor stops produces an increase in emissions. HC emissions show the strongest dependence on delay and stops, while NO and CO emissions show a weaker dependence.For the most part, the results of the before and after study showed no statistically significant changes in traffic parameters (speed, delay, and stops). As a result, no statistically significant changes occurred in the vehicle emissions. However, when arranging the data into groups of congested and uncongested runs, a significant direct relationship was found between HC emissions and traffic congestion. NO and CO emissions did not change significantly, even with significant changes in traffic congestion.Overall, this thesis presents a first-of-a-kind investigation into the trends between traffic parameters and real-world, on-road vehicle emissions.

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