Impact of stochasticity on platoon stability of car-following models for emissions estimation

Abstract

In the application of microscopic traffic simulations for vehicle emissions modeling, the reality and platoon stability of vehicle trajectories derived from the car-following component have been questioned. This study compared the platoon stability of the Gipps car-following model, the full velocity difference model (FVDM), the intelligent driver model (IDM), and the Wiedemann model for emissions modeling and proposed the modified Gipps model by incorporating stochastic parameters. The results indicated the superior performance of the FVDM and IDM for emissions estimation compared with the Wiedemann model, and the emissions estimation errors were stable along the platoon for the above models. Gipps model generated realistic vehicle dynamics of the first following vehicle; however, the emissions estimation errors increased along the platoon. After the optimization of the Gipps model by incorporating stochastic parameters, the root-mean-square error (RMSE) of acceleration distribution, RMSE of vehicle specific power (VSP) distribution and relative error of emission factor were reduced by 5.00%, 2.52% and 11.04%, respectively, and the standard deviations of the errors in the platoon were 0.18%, 0.08% and 0.86%, respectively. The stochastic parameters were proven to potentially improve the reality of simulated trajectory and the platoon stability of the Gipps model for accurate emissions modeling.

Keywords

car-following model / platoon stability / stochasticity / emissions estimation / VSP distribution

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