Search

This study derived two models to estimate emissions on the basis of macroscopic mobility measures. The developed models can be used as part of signal timing optimization, macroscopic and mesoscopic simulation, cost-benefit analysis, and real-time and off-line estimation of arterial road performance. The derivation relied on output from the Motor Vehicle Emission Simulator model operating mode distribution analysis and used estimates from microscopic simulation model runs as input. Models with various combinations of independent variables were tested and two final models were selected. The first model used vehicle miles traveled (VMT) and vehicle delays as independent variables. The second model used VMT, vehicle delays, stop delays, and number of stops. Both models showed acceptable performance for most of the investigated cases in simulation modeling. A further test was performed using vehicle trajectories from the next generation simulation program databases. The results showed that the model developed on the basis of VMT and total vehicle delays performed well. However, the second model, developed on the basis of VMT, total vehicle delays, total stop delays, and number of stops, did not perform well. This could be because the model required accurate vehicle trajectories, including accurate acceleration and deceleration estimates. The quality of the trajectories in microscopic simulation is expected to affect the accuracy of the second model.

This study derived two models to estimate emissions on the basis of macroscopic mobility measures. The developed models can be used as part of signal timing optimization, macroscopic and mesoscopic simulation, cost-benefit analysis, and real-time and off-line estimation of arterial road performance. The derivation relied on output from the Motor Vehicle Emission Simulator model operating mode distribution analysis and used estimates from microscopic simulation model runs as input. Models with various combinations of independent variables were tested and two final models were selected. The first model used vehicle miles traveled (VMT) and vehicle delays as independent variables. The second model used VMT, vehicle delays, stop delays, and number of stops. Both models showed acceptable performance for most of the investigated cases in simulation modeling. A further test was performed using vehicle trajectories from the next generation simulation program databases. The results showed that the model developed on the basis of VMT and total vehicle delays performed well. However, the second model, developed on the basis of VMT, total vehicle delays, total stop delays, and number of stops, did not perform well. This could be because the model required accurate vehicle trajectories, including accurate acceleration and deceleration estimates. The quality of the trajectories in microscopic simulation is expected to affect the accuracy of the second model.