The next generation motor vehicle emission rate model used in the United States Environmental Protection Agency’s Motor Vehicle Emission Simulator (MOVES) requires second-by-second vehicle data in order to fully utilize model capabilities. However, field data collection of this type of data is resource intensive and frequently not realistic for local agencies.
Some microsimulation models have the capability of outputting instantaneous speed and acceleration, which can be used in MOVES. With these capabilities, microsimulation offers a valuable tool to conduct analyses requiring a large number of data. However, simulation models usually employ theoretical profiles for the relationship between acceleration and speed. The algorithms were intended to model gross measures of traffic activity, such as changes in cycle length or the effect of an incident. Model output, however, remains unvalidated for predicting the level of vehicle activity output required for MOVES.
Collecting field data to calibrate Vissim models is often expensive and not always feasible. The use of a driving simulator provides an additional way to provide these data. A simulator has advantages over field data in that it can be used to collect data for new projects where field data cannot be collected. Simulators also allow for complete control over interactions between the driver and other vehicles.
Two case studies were used to assess the utility of the microsimulation model, Vissim, in developing output that can be used as input to MOVES. In one scenario, drivers were selected to drive an instrumented test vehicle along a test corridor. In another scenario, five drivers drove through a roundabout in the University of Iowa National Advanced Driving Simulator (NADS).
Models for each scenario were also developed in Vissim. Model output was compared to field collected speed/acceleration profile data to assess the accuracy of microsimulation models in providing realistic estimates of vehicle activity as input to MOVES. Results were summarized to demonstrate the applicability of linking microsimulated vehicle activity data with emissions models to better estimate the emission impacts of different transportation strategies.