A study design procedure was developed and demonstrated for the deployment of portable onboard tailpipe emissions measurement systems for selected highway vehicles fueled by gasoline and E85 (a blend of 85% ethanol and 15% gasoline). Data collection, screening, processing, and analysis protocols were developed to assure data quality and to provide insights regarding quantification of real-world intravehicle variability in hot-stabilized emissions. Onboard systems provide representative real-world emissions measurements; however, onboard field studies are challenged by the observable but uncontrollable nature of traffic flow and ambient conditions. By characterizing intravehicle variability based on repeated data collection runs with the same driver/vehicle/route combinations, this study establishes the ability to develop stable modal emissions rates for idle, acceleration, cruise, and deceleration even in the face of uncontrollable external factors. For example, a consistent finding is that average emissions during acceleration are typically 5 times greater than during idle for hydrocarbons and carbon dioxide and 10 times greater for nitric oxide and carbon monoxide. A statistical method for comparing on-road emissions of different drivers is presented. Onboard data demonstrate the importance of accounting for the episodic nature of real-world emissions to help develop appropriate traffic and air quality management strategies. INTRODUCTIONMotor vehicle emissions contribute substantially to national and local emission inventories for hydrocarbons (HCs), nitrogen oxides (NO x ), and carbon monoxide (CO). 1-3 The typical approach for estimating vehicle emissions is to use area-wide driving-cycle-based models such as MOBILE5b, MOBILE6, and EMFAC. The tailpipe emissions data for these models are typically based on average emissions per mile over standard driving cycles as measured in the laboratory using a dynamometer. Idle emissions are typically extrapolated from a g/mi basis based on driving cycles with low average speeds to a g/sec basis but are not estimated based on measurement of actual idling. A key hypothesis of this work is that the emission rate during idling is substantially lower than for other driving modes. Second-by-second data collected in the laboratory and on the road demonstrate that vehicle emissions are episodic in nature, indicating that average emissions for a trip are often dominated by short-term events. Thus, while driving-cycle-based models are useful for developing area-wide emission inventories, these models lack the temporal and spatial resolution to properly characterize the episodic microscale nature of vehicle emissions. The latter is a critical need to identify and develop effective traffic management strategies that will result in real-world emissions reductions. Furthermore, the standard driving cycles may not adequately represent real-world driving for a particular location because of failure to represent the influence of real-world traffic flow. Therefore, it is importan...

The objective here is to quantify the variability in emissions of selected light duty gasoline vehicles by routes, time of day, road grade, and vehicle with a focus on the impact of routes and road grade. Field experiments using a portable emission measurement system were conducted under real-world driving cycles. The study area included two origin/destination pairs, each with three alternative routes. Total emissions varied from trip to trip and from route to route due to variations in average speed and travel time. On an average trip basis, the total NO emissions differed by 24% when comparing alternative routes and by 19% when comparing congested travel time with less congested traffic time. Positive road grades were associated with an approximately 20% increase in localized emissions rates, while negative road grades were associated with a similar relative decrease. The average vehicle-specific power based NO modal emission rates differed by more than 2 orders of magnitude when comparing different vehicles. The results demonstrate that alternative routing can significantly impact trip emissions. Furthermore, road grade should be taken into account for localized emissions estimation. Vehicle-specific models are needed to capture episodic effects of emissions for near-road short-term human exposure assessment.

Emissions during a trip often depend on transient vehicle dynamics that influence the instantaneous engine load. Vehicle specific power (VSP) is a proxy variable for engine load that has been shown to be highly correlated with emissions. This study estimates roadway link average emission rates for diesel-fueled transit buses based on link mean speeds, using newly defined VSP modes from data gathered by a portable emissions monitoring system. Speed profiles were categorized by facility type and mean travel speed, and stratified into discrete VSP modes. VSP modal average emission rates and the time spent in the corresponding VSP modes were then used to make aggregate estimates of total and average emission rates for a road link. The average emission rates were sensitive to link mean speed, but not to facility type. A recommendation is made regarding the implementation of link average emission rates in conjunction with transportation models for the purpose of estimating regional emissions for diesel transit buses.

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This research explores factors associated with driver yielding behavior at unsignalized pedestrian crossings and develops predictive models for yielding using logistic regression. It considers the effect of variables describing driver attributes, pedestrian characteristics and concurrent conditions at the crosswalk on the yield response. Special consideration is given to ‘vehicle dynamics constraints’ that form a threshold for the potential to yield. Similarities are identified to driver reaction in response to the ‘amber’ indication at a signalized intersection. The logit models were developed from data collected at two unsignalized mid-block crosswalks in North Carolina. The data include ‘before’ and ‘after’ observations of two pedestrian safety treatments, an in-street pedestrian crossing sign and pedestrian-actuated in-roadway warning lights. The analysis suggests that drivers are more likely to yield to assertive pedestrians who walk briskly in their approach to the crosswalk. In turn, the yield probability is reduced with higher speeds, deceleration rates and if vehicles are traveling in platoons. The treatment effects proved to be significant and increased the propensity of drivers to yield, but their effectiveness may be dependent on whether the pedestrian activates the treatment. The results of this research provide new insights on the complex interaction of pedestrians and vehicles at unsignalized intersections and have implications for future work towards predictive models for driver yielding behavior. The developed logit models can provide the basis for representing driver yielding behavior in a microsimulation modeling environment.