Traffic flow characterization is vital for understanding in the era of intelligent vehicles (IVs). This study investigates the impact of IVs on mixed traffic using the classical Intelligent Driver Model (IDM). Human-driven vehicles (HVs) generally maintain larger time headways, resulting in slower traffic evolution and delayed dissipation of disturbances, whereas IVs sustain smaller headways, which allows faster damping of disturbances and improved stability. Simulations on a 2000 m ring road with 15 vehicles, where one vehicle was forced to decelerate for 4 s, were used to evaluate shockwave formation, propagation, and dissipation. Results show that a higher 80% penetration of IVs dissipating disturbances within 60 s compared to over 150 s for HVs speed stability, reduces peak speed variance. Findings confirm the stabilizing role of IVs in improving traffic flow efficiency and resilience, highlighting the need for realistic \(\delta \) calibration to accurately model mixed traffic conditions.