The Electric Vehicle Model (EVM): A Novel Car-Following Model for Electric Adaptive Cruise Control Vehicles

Electric vehicle (EV) adoption is accelerating across the automotive industry. The first generation of electrified vehicles with driver assistance features like adaptive cruise control (ACC) are now commercially available. While studies have highlighted the sustainability benefits of EVs, recent research suggests these EVs may impact traffic flow differently than traditional internal combustion engine (ICE) vehicles since they have distinct driving dynamics. Understanding the differences between EV-ACC and ICE-ACC vehicle driving behaviors and their effects on traffic flow remains an important research gap. To address this gap, we leverage a recently published EV-ACC dataset and develop a new microscopic car-following model, namely the electric vehicle model (EVM), to understand EV-ACC driving behavior. The proposed model is calibrated using batch optimization and outperforms other commonly used car-following models in capturing EV-ACC car-following patterns. Moreover, we use a simulation of a string of EV-ACC vehicles behaving based on the parameter values of the EVM model to demonstrate their ability to reduce traffic oscillations compared to the commonly used car-following models.