A Comparative Study of Oscillatory Perturbations in Car-Following Models

As connected and autonomous vehicles become more widespread, platooning has emerged as a key strategy to improve road capacity, reduce fuel consumption, and enhance traffic flow. However, the benefits of platoons strongly depend on their ability to maintain stability. Instability can lead to unsafe spacing and increased energy usage. In this work, we study platoon instability and analyze the root cause of its occurrence, as well as its impacts on the following vehicle. To achieve this, we propose a comparative study between different car-following models such as the Intelligent Driver Model (IDM), the Optimal Velocity Model (OVM), the General Motors Model (GMM), and the Cooperative Adaptive Cruise Control (CACC). In our approach, we introduce a disruption in the model by varying the velocity of the leading vehicle to visualize the behavior of the following vehicles. To evaluate the dynamic response of each model, we introduce controlled perturbations in the velocity of the leading vehicle, specifically, sinusoidal oscillations and discrete velocity changes. The resulting vehicle trajectories and variations in inter-vehicle spacing are analyzed to assess the robustness of each model to disturbance propagation. The findings offer insight into model sensitivity, stability characteristics, and implications for designing resilient platooning control strategies.