This study investigates the response times of autonomous vehicles (AVs) equipped with adaptive cruise control (ACC) and traditional human-driven vehicles (TVs) in mixed traffic scenarios. The primary objective is to assess how these response times impact the stability and safety of mixed traffic flow, considering the growing prevalence of ACC technology in vehicles worldwide. Utilising a trajectory dataset from OpenACC totalling 3389.70 s, this research introduces a response time estimation framework that combines cross-correlation and partial autocorrelation techniques. The study calibrates Gazis, Herman, and Rothery's (GHR) car-following model to evaluate mixed traffic flow stability and employs a modified time-to-collision (MTTC) surrogate for safety analysis. The study also delves into the influence of vehicle manufacturer diversity on study outcomes. Key findings reveal that the AVs exhibit significantly longer response times, ranging from 1.10–3.20 s, compared to the 0.30–1.90-second range of traditional vehicles (p value < 0.005). These extended response times in AVs contribute to prolonged traffic flow instability and increased traffic conflicts. Moreover, the type of lead vehicle does not significantly affect the response times of either AVs or TVs (p value > 0.005). The study also highlights that vehicle manufacturer diversity does not substantially affect these response times. Additionally, the examination of fitted GHR parameters underscores AVs’ heightened sensitivity to spacing and relative speed, providing insights into AV dynamics in the presence of mixed traffic.