This paper addresses the modeling challenge of significant asymmetry between acceleration and deceleration processes in car-following behavior by proposing an Asymmetric Acceleration and Deceleration Car Following (AAD-CF) model. The model characterizes driving decisions using both desired speed and desired spacing, and incorporates an asymmetric correction factor to capture differences in acceleration and deceleration behavior. Based on real vehicle trajectory data from the I-80 dataset, the model was compared at the microscopic level against classical models such as Gipps in terms of trajectory fitting error. The results show that the AAD-CF model consistently achieves lower trajectory fitting errors across different simulation time-steps, with error reduction exceeding 10%. At the macroscopic traffic flow level, the model successfully reproduced three-phase traffic flow states—free flow, synchronized flow, and wide moving jams. By implementing both startup and emergency braking scenarios, it was further revealed that braking waves propagate approximately 40% faster than startup waves, demonstrating asymmetric wave propagation. This study provides quantitative evidence for understanding the intrinsic relationship between microscopic driving behavior and macroscopic traffic phenomena, and the proposed model can support traffic simulation systems and theoretical analysis.
Xing et al. (Wed,) studied this question.