TRIM: Platform-Independent Framework for Speed Trajectory Refinement in Emission Modeling

Abstract

Traffic microsimulation routinely generates second-by-second speed trajectories that contain nonphysical fluctuations in acceleration and jerk, which can lead to systematic overestimation of vehicular emissions. This study presents Trajectory Refinement for Emission Modeling (TRIM), a platform-independent post-processing framework that refines microsimulated trajectories through physics-based optimization. By enforcing acceleration-dependent jerk constraints, car-following safety constraints, and trajectory-consistency within a mixed-integer quadratic programming formulation, TRIM transforms raw simulation outputs into physically plausible, emission-consistent trajectories. Validated against high-resolution unmanned aerial vehicle-derived ground truth under three car-following models (Wiedemann 99, Krauss, and the Intelligent Driver Model), TRIM reduces total emission errors within 9% for nitrogen oxides and 7% for PM 2.5 , with spatial errors predominantly within ±20% (±10% midblock). The platform-independent framework provides a transferable pathway for standardized emission assessment across simulation platforms, with an open-source implementation publicly available.