Estimating impacts of emission specific characteristics on vehicle operation for quantifying air pollutant emissions and energy use

- Model predicts the fraction of time vehicles spend in various operating conditions.
- The output can be used to estimate air pollutant emissions and energy use.
- Authors combine micro-simulation for vehicle operations with structural equations.
- Geometric design elements have the largest influence on link speed.
- Most impact on vehicle operation, speed limit, then facility type and driving style, have been found.

This paper proposes and illustrates a methodology to predict the fraction of time motor vehicles spend in different operating conditions from readily observable variables called emission specific characteristics (ESC). ESC describe salient characteristics of vehicles, roadway geometry, the roadside environment, traffic, and driving style (aggressive, normal, and calm). The information generated by our methodology can then be entered in vehicular emission models that rely on vehicle specific power, i.e., comprehensive modal emissions model (CMEM), international vehicle emissions (IVE), or motor vehicle emission simulator (MOVES) to compute energy consumption and vehicular emissions for various air pollutants. After generating second-by-second vehicle trajectories from a calibrated micro-simulation model, the authors estimated structural equation models to examine the influence of link ESC on vehicle operation. Authors' results show that 67% of the link speed variance is explained by ESC. Overall, the roadway geometry exerts a greater influence on link speed than traffic characteristics, the roadside environment, and driving style. Moreover, the speed limit has the strongest influence on vehicle operation, followed by facility type and driving style. Better understanding the impact on vehicle operation of ESC could help metropolitan planning organizations (MPOs) and regional transportation authorities predict vehicle operations and reduce the environmental footprint of motor vehicles.