This<?show [AQ ID=Q1]?>study is focused on the design of cooperative adaptive cruise control (CACC) to regulate the longitudinal motion of connected and automated vehicles (CAVs) in mixed traffic that is composed of human‐driven vehicles and CAVs. Wireless vehicle‐to‐vehicle communication is exploited to monitor the motion of multiple broadcasting vehicles, and a strategy is designed to determine whether the received data of other vehicles are incorporated into CACC. A condition is derived for choosing control gains that ensure the internal stability of CAVs in the presence of time delays and switching connectivity topologies of information flow. Moreover, because the switching connectivity topologies may change the dynamics of the whole vehicle chain, the authors apply a data‐driven approach for online optimisation of control gains such that CACC adapts to the variations of connectivity topologies. The proposed selective CACC is validated through numerical simulations. To enhance the fidelity of simulations, they use the data collected through on‐road experiments to simulate the motion of human‐driven vehicles and apply the physics‐based vehicle dynamic model to simulate the motion of CAVs. Simulation results demonstrate the advantages of the proposed selective CACC in improving vehicle safety and in mitigating perturbations in mixed traffic.